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Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.

ICRA@40: 23–26 September 2024, ROTTERDAM, NETHERLANDSIROS 2024: 14–18 October 2024, ABU DHABI, UAEICSR 2024: 23–26 October 2024, ODENSE, DENMARKCybathlon 2024: 25–27 October 2024, ZURICH

Enjoy today’s videos!

If the Italian Institute of Technology’s iRonCub3 looks this cool while learning to fly, just imagine how cool it will look when it actually takes off!

Hovering is in the works, but this is a really hard problem, which you can read more about in Daniele Pucci’s post on LinkedIn.

[ LinkedIn ]

Stanford Engineering and the Toyota Research Institute achieve the world’s first autonomous tandem drift. Leveraging the latest AI technology, Stanford Engineering and TRI are working to make driving safer for all. By automating a driving style used in motorsports called drifting—in which a driver deliberately spins the rear wheels to break traction—the teams have unlocked new possibilities for future safety systems.

[ TRI ]

Researchers at the Istituto Italiano di Tecnologia (Italian Institute of Technology) have demonstrated that under specific conditions, humans can treat robots as coauthors of the results of their actions. The condition that enables this phenomenon is a robot that behaves in a social, humanlike manner. Engaging in eye contact and participating in a common emotional experience, such as watching a movie, are key.

[ Science Robotics ]

If Aibo is not quite catlike enough for you, here you go.

[ Maicat ] via [ RobotStart ]

I’ve never been more excited for a sim-to-real gap to be bridged.

[ USC Viterbi ]

I’m sorry, but this looks exactly like a quadrotor sitting on a test stand.

The 12-pound Quad-Biplane combines four rotors and two wings without any control surfaces. The aircraft takes off like a conventional quadcopter and transitions to a more-efficient horizontal cruise flight, similar to that of a biplane. This combines the simplicity of a quadrotor design, providing vertical flight capability, with the cruise efficiency of a fixed-wing aircraft. The rotors are responsible for aircraft control both in vertical and forward cruise flight regimes.

[ AVFL ]

Tensegrity robots are so weird, and I so want them to be useful.

[ Suzumori Endo Lab ]

Top-performing robots need all the help they can get.

[ Team B-Human ]

And now: a beetle nearly hit by an autonomous robot.

[ WVUIRL ]

Humans possess a remarkable ability to react to unpredictable perturbations through immediate mechanical responses, which harness the visco-elastic properties of muscles to maintain balance. Inspired by this behavior, we propose a novel design of a robotic leg utilizing fiber-jammed structures as passive compliant mechanisms to achieve variable joint stiffness and damping.

[ Paper ]

I don’t know what this piece of furniture is, but your cats will love it.

[ ABB ]

This video shows a dexterous avatar humanoid robot with VR teleoperation, hand tracking, and speech recognition to achieve highly dexterous mobile manipulation. Extend Robotics is developing a dexterous remote-operation interface to enable data collection for embodied AI and humanoid robots.

[ Extend Robotics ]

I never really thought about this, but wind turbine blades are hollow inside and need to be inspected sometimes, which is really one of those jobs where you’d much rather have a robot do it.

[ Flyability ]

Here’s a full, uncut drone-delivery mission, including a package pickup from our AutoLoader—a simple, nonpowered mechanical device that allows retail partners to utilize drone delivery with existing curbside-pickup workflows.

[ Wing ]

Daniel Simu and his acrobatic robot competed in “America’s Got Talent,” and even though his robot did a very robot thing by breaking itself immediately beforehand, the performance went really well.

[ Acrobot ]

A tour of the Creative Robotics Mini Exhibition at the Creative Computing Institute, University of the Arts London.

[ UAL ]

Thanks, Hooman!

Zoox CEO Aicha Evans and cofounder and chief technology officer Jesse Levinson hosted a LinkedIn Live last week to reflect on the past decade of building Zoox and their predictions for the next 10 years of the autonomous-vehicle industry.

[ Zoox ]



This is a sponsored article brought to you by Elephant Robotics.

Elephant Robotics has gone through years of research and development to accelerate its mission of bringing robots to millions of homes and a vision of “Enjoy Robots World”. From the collaborative industrial robots P-series and C-series, which have been on the drawing board since its establishment in 2016, to the lightweight desktop 6 DOF collaborative robot myCobot 280 in 2020, to the dual-armed, semi-humanoid robot myBuddy, which was launched in 2022, Elephant Robotics is launching 3-5 robots per year, and this year’s full-body humanoid robot, the Mercury series, promises to reshape the landscape of non-human workers, introducing intelligent robots like Mercury into research and education and even everyday home environments.

A Commitment to Practical Robotics

Elephant Robotics proudly introduces the Mercury Series, a suite of humanoid robots that not only push the boundaries of innovation but also embody a deep commitment to practical applications. Designed with the future of robotics in mind, the Mercury Series is poised to become the go-to choice for researchers and industry professionals seeking reliable, scalable, and robust solutions.


Elephant Robotics

The Genesis of Mercury Series: Bridging Vision With Practicality

From the outset, the Mercury Series has been envisioned as more than just a collection of advanced prototypes. It is a testament to Elephant Robotics’ dedication to creating humanoid robots that are not only groundbreaking in their capabilities but also practical for mass production and consistent, reliable use in real-world applications.

Mercury X1: Wheeled Humanoid Robot

The Mercury X1 is a versatile wheeled humanoid robot that combines advanced functionalities with mobility. Equipped with dual NVIDIA Jetson controllers, lidar, ultrasonic sensors, and an 8-hour battery life, the X1 is perfect for a wide range of applications, from exploratory studies to commercial tasks requiring mobility and adaptability.

Mercury B1: Dual-Arm Semi-Humanoid Robot

The Mercury B1 is a semi-humanoid robot tailored for sophisticated research. It features 17 degrees of freedom, dual robotic arms, a 9-inch touchscreen, a NVIDIA Xavier control chip, and an integrated 3D camera. The B1 excels in machine vision and VR-assisted teleoperation, and its AI voice interaction and LLM integration mark significant advancements in human-robot communication.

These two advanced models exemplify Elephant Robotics’ commitment to practical robotics. The wheeled humanoid robot Mercury X1 integrates advanced technology with a state-of-the-art mobile platform, ensuring not only versatility but also the feasibility of large-scale production and deployment.

Embracing the Power of Reliable Embodied AI

The Mercury Series is engineered as the ideal hardware platform for embodied AI research, providing robust support for sophisticated AI algorithms and real-world applications. Elephant Robotics demonstrates its commitment to innovation through the Mercury series’ compatibility with NVIDIA’s ISSACSIM, a state-of-the-art simulation platform that facilitates sim2real learning, bridging the gap between virtual environments and physical robot interaction.

The Mercury Series is perfectly suited for the study and experimentation of mainstream large language models in embodied AI. Its advanced capabilities allow seamless integration with the latest AI research. This provides a reliable and scalable platform for exploring the frontiers of machine learning and robotics.

Furthermore, the Mercury Series is complemented by the myArm C650, a teleoperation robotic arm that enables rapid acquisition of physical data. This feature supports secondary learning and adaptation, allowing for immediate feedback and iterative improvements in real-time. These features, combined with the Mercury Series’ reliability and practicality, make it the preferred hardware platform for researchers and institutions looking to advance the field of embodied AI.

The Mercury Series is supported by a rich software ecosystem, compatible with major programming languages, and integrates seamlessly with industry-standard simulation software. This comprehensive development environment is enhanced by a range of auxiliary hardware, all designed with mass production practicality in mind.

Elephant Robotics

Drive to Innovate: Mass Production and Global Benchmarks

The “Power Spring” harmonic drive modules, a hallmark of the Elephant Robotics’ commitment to innovation for mass production, have been meticulously engineered to offer an unparalleled torque-to-weight ratio. These components are a testament to the company’s foresight in addressing the practicalities of large-scale manufacturing. The incorporation of carbon fiber in the design of these modules not only optimizes agility and power but also ensures that the robots are well-prepared for the rigors of the production line and real-world applications. The Mercury Series, with its spirit of innovation, is making a significant global impact, setting a new benchmark for what practical robotics can achieve.

Elephant Robotics is consistently delivering mass-produced robots to a range of renowned institutions and industry leaders, thereby redefining the industry standards for reliability and scalability. The company’s dedication to providing more than mere prototypes is evident in the active role its robots play in various sectors, transforming industries that are in search of dependable and efficient robotic solutions.

Conclusion: The Mercury Series—A Beacon for the Future of Practical Robotics

The Mercury Series represents more than a product; it is a beacon for the future of practical robotics. Elephant Robotics’ dedication to affordability, accessibility, and technological advancement ensures that the Mercury Series is not just a research tool but a platform for real-world impact.

Mercury Usecases | Explore the Capabilities of the Wheeled Humanoid Robot and Discover Its Precision youtu.be

Elephant Robotics: https://www.elephantrobotics.com/en/

Mercury Robot Series: https://www.elephantrobotics.com/en/mercury-humanoid-robot/



The dream of robotic floor care has always been for it to be hands-off and mind-off. That is, for a robot to live in your house that will keep your floors clean without you having to really do anything or even think about it. When it comes to robot vacuuming, that’s been more or less solved thanks to self-emptying robots that transfer debris into docking stations, which iRobot pioneered with the Roomba i7+ in 2018. By 2022, iRobot’s Combo j7+ added an intelligent mopping pad to the mix, which definitely made for cleaner floors but was also a step backwards in the sense that you had to remember to toss the pad into your washing machine and fill the robot’s clean water reservoir every time. The Combo j9+ stuffed a clean water reservoir into the dock itself, which could top off the robot with water by itself for a month.

With the new Roomba Combo 10 Max, announced today, iRobot has cut out (some of) that annoying process thanks to a massive new docking station that self empties vacuum debris, empties dirty mop water, refills clean mop water, and then washes and dries the mopping pad, completely autonomously.

iRobot

The Roomba part of this is a mildly upgraded j7+, and most of what’s new on the hardware side here is in the “multifunction AutoWash Dock.” This new dock is a beast: It empties the robot of all of the dirt and debris picked up by the vacuum, refills the Roomba’s clean water tank from a reservoir, and then starts up a wet scrubby system down under the bottom of the dock. The Roomba deploys its dirty mopping pad onto that system, and then drives back and forth while the scrubby system cleans the pad. All the dirty water from this process gets sucked back up into a dedicated reservoir inside the dock, and the pad gets blow dried while the scrubby system runs a self-cleaning cycle.

The dock removes debris from the vacuum, refills it with clean water, and then uses water to wash the mopping pad.iRobot

This means that as a user, you’ve only got to worry about three things: dumping out the dirty water tank every week (if you use the robot for mopping most days), filling the clean water tank every week, and then changing out the debris back every two months. That is not a lot of hands-on time for having consistently clean floors.

The other thing to keep in mind about all of these robots is that they do need relatively frequent human care if you want them to be happy and successful. That means flipping them over and getting into their guts to clean out the bearings and all that stuff. iRobot makes this very easy to do, and it’s a necessary part of robot ownership, so the dream of having a robot that you can actually forget completely is probably not achievable.

The consequence for this convenience is a real chonker of a dock. The dock is basically furniture, and to their credit iRobot designed it so that the top surface is useable as a shelf—Access to the guts of the dock are from the front, not the top. This is fine, but it’s also kind of crazy just how much these docks have expanded, especially once you factor in the front ramp that the robot drives up, which sticks out even farther.

The Roomba will detect carpet and lift its mopping pad up to prevent drips.iRobot

We asked iRobot Director of Project Management Warren Fernandez about whether docks are just going to keep on getting bigger forever until we’re all just living in giant robot docks, to which he said: “Are you going to continue to see some large capable multi-function docks out there in the market? Yeah, I absolutely think you will—but when does big become too big?” Fernandez says that there are likely opportunities to reduce dock size going forward through packaging efficiencies or dual-purpose components, but that there’s another option, too: Distributed docks. “If a robot has dry capabilities and wet capabilities, do those have to coexist inside the same chassis? What if they were separate?” says Fernandez.

We should mention that iRobot is not the first in the robotic floor care robot space to have a self-cleaning mop, and they’re also not the first to think about distributed docks, although as Fernandez explains, this is a more common approach in Asia where you can also take advantage of home plumbing integration. “It’s a major trend in China, and starting to pop up a little bit in Europe, but not really in North America yet. How amazing could it be if you had a dock that, in a very easy manner, was able to tap right into plumbing lines for water supply and sewage disposal?”

According to Fernandez, this tends to be much easier to do in China, both because the labor cost for plumbing work is far lower than in the U.S. and Europe, and also because it’s fairly common for apartments in China to have accessible floor drains. “We don’t really yet see it in a major way at a global level,” Fernandez tells us. “But that doesn’t mean it’s not coming.”

The robot autonomously switches mopping mode on and off for different floor surfaces.iRobot

We should also mention the Roomba Combo 10 Max, which includes some software updates:

  • The front-facing camera and specialized bin sensors can identify dirtier areas eight times as effectively as before.
  • The Roomba can identify specific rooms and prioritize the order they’re cleaned in, depending on how dirty they get.
  • A new cleaning behavior called “Smart Scrub” adds a back-and-forth scrubbing motion for floors that need extra oomph.

And here’s what I feel like the new software should do, but doesn’t:

  • Use the front-facing camera and bin sensors to identify dirtier areas and then autonomously develop a schedule to more frequently clean those areas.
  • Activate Smart Scrub when the camera and bin sensors recognize an especially dirty floor.

I say “should do” because the robot appears to be collecting the data that it needs to do these things but it doesn’t do them yet. New features (especially new features that involve autonomy) take time to develop and deploy, but imagine a robot that makes much more nuanced decisions about where and when to clean based on very detailed real-time data and environmental understanding that iRobot has already implemented.

I also appreciate that even as iRobot is emphasizing autonomy and leveraging data to start making more decisions for the user, the company is also making sure that the user has as much control as possible through the app. For example, you can set the robot to mop your floor without vacuuming first, even though if you do that, all you’re going to end up with a much dirtier mop. Doesn’t make a heck of a lot of sense, but if that’s what you want, iRobot has empowered you to do it.

The dock opens from the front for access to the clean and dirty water storage and the dirt bag.iRobot

The Roomba Combo 10 Max will be launching in August for US $1,400. That’s expensive, but it’s also how iRobot does things: A new Roomba with new tech always gets flagship status and premium cost. Sooner or later it’ll be affordable enough that the rest of us will be able to afford it, too.



Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.

ICRA@40: 23–26 September 2024, ROTTERDAM, NETHERLANDSIROS 2024: 14–18 October 2024, ABU DHABI, UAEICSR 2024: 23–26 October 2024, ODENSE, DENMARKCybathlon 2024: 25–27 October 2024, ZURICH

Enjoy today’s videos!

Perching with winged Unmanned Aerial Vehicles has often been solved by means of complex control or intricate appendages. Here, we present a method that relies on passive wing morphing for crash-landing on trees and other types of vertical poles. Inspired by the adaptability of animals’ and bats’ limbs in gripping and holding onto trees, we design dual-purpose wings that enable both aerial gliding and perching on poles.

[ Nature Communications Engineering ]

Pretty impressive to have low enough latency in controlling your robot’s hardware that it can play ping pong, although it makes it impossible to tell whether the robot or the human is the one that’s actually bad at the game.

[ IHMC ]

How to be a good robot when boarding an elevator.

[ NAVER ]

Have you ever wondered how insects are able to go so far beyond their home and still find their way? The answer to this question is not only relevant to biology but also to making the AI for tiny, autonomous robots. We felt inspired by biological findings on how ants visually recognize their environment and combine it with counting their steps in order to get safely back home.

[ Science Robotics ]

Team RoMeLa Practice with ARTEMIS humanoid robots, featuring Tsinghua Hephaestus (Booster Alpha). Fully autonomous humanoid robot soccer match with the official goal of beating the human WorldCup Champions by the year 2050.

[ RoMeLa ]

Triangle is the most stable shape, right?

[ WVU IRL ]

We propose RialTo, a new system for robustifying real-world imitation learning policies via reinforcement learning in “digital twin” simulation environments constructed on the fly from small amounts of real-world data.

[ MIT CSAIL ]

There is absolutely no reason to watch this entire video, but Moley Robotics is still working on that robotic kitchen of theirs.

I will once again point out that the hardest part of cooking (for me, anyway) is the prep and the cleanup, and this robot still needs you to do all that.

[ Moley ]

B-Human has so far won 10 titles at the RoboCup SPL tournament. Can we make it 11 this year? Our RoboCup starts off with a banger game against HTWK Robots form Leipzig!

[ Team B-Human ]

AMBIDEX is a dual-armed robot with an innovative mechanism developed for safe coexistence with humans. Based on an innovative cable structure, it is designed to be both strong and stable.

[ NAVER ]

As NASA’s Perseverance rover prepares to ascend to the rim of Jezero Crater, its team is investigating a rock unlike any that they’ve seen so far on Mars. Deputy project scientist Katie Stack Morgan explains why this rock, found in an ancient channel that funneled water into the crater, could be among the oldest that Perseverance has investigated—or the youngest.

[ NASA ]

We present a novel approach for enhancing human-robot collaboration using physical interactions for real-time error correction of large language model (LLM) parameterized commands.

[ Figueroa Robotics Lab ]

Husky Observer was recently used to autonomously inspect solar panels at a large solar panel farm. As part of its mission, the robot navigated rows of solar panels, stopping to inspect areas with its integrated thermal camera. Images were taken by the robot and enhanced to detect potential “hot spots” in the panels.

[ Clearpath Robotics ]

Most of the time, robotic workcells contain just one robot, so it’s cool to see a pair of them collaborating on tasks.

[ Leverage Robotics ]

Thanks, Roman!

Meet Hydrus, the autonomous underwater drone revolutionising underwater data collection by eliminating the barriers to its entry. Hydrus ensures that even users with limited resources can execute precise and regular subsea missions to meet their data requirements.

[ Advanced Navigation ]

Those adorable Disney robots have finally made their way into a paper.

[ RSS 2024 ]



Cigarette butts are the second most common undisposed-of litter on Earth—of the six trillion-ish cigarettes inhaled every year, it’s estimated that at over four trillion of the butts are just tossed onto the ground, each one leeching over 700 different toxic chemicals into the environment. Let’s not focus on the fact that all those toxic chemicals are also going into people’s lungs, and instead talk about the ecosystem damage that they can do and also just the general grossness of having bits of sucked-on trash everywhere. Ew.

Preventing those cigarette butts from winding up on the ground in the first place would be the best option, but would require a pretty big shift in human behavior. Operating under the assumption that humans changing their behavior is a non-starter, roboticists from the Dynamic Legged Systems unit at the Italian Institute of Technology (IIT) in Genoa have instead designed a novel platform for cigarette butt cleanup in the form of a quadrupedal robot with vacuums attached to its feet.

IIT

There are, of course, far more efficient ways of at least partially automating the cleanup of litter with machines. The challenge is that most of that automation relies on mobility systems with wheels, which won’t work on the many beautiful beaches (and many beautiful flights of stairs) of Genoa. In places like these, it still falls to humans to do the hard work, which is less than ideal.

This robot, developed in Claudio Semini’s lab at IIT, is called VERO (Vacuum-cleaner Equipped RObot). It’s based around an AlienGo from Unitree, with a commercial vacuum mounted on its back. Hoses go from the vacuum down the leg to each foot, with a custom 3D printed nozzle that puts as much suction near the ground as possible without tripping the robot up. While the vacuum is novel, the real contribution here is how the robot autonomously locates things on the ground and then plans out how to interact with those things using its feet.

First, an operator designates an area for VERO to clean, after which the robot operates by itself. After calculating an exploration path to explore the entire area, the robot uses its onboard cameras and a neural network to detect cigarette butts. This is trickier than it sounds, because there may be a lot of cigarette butts on the ground, and they all probably look pretty much the same, so the system has to filter out all of the potential duplicates. The next step is to plan out its next steps—VERO has to plan footsteps to put the vacuum side of one of its feet right next to each cigarette butt, while calculating a safe, stable pose for the rest of its body. Since this whole process can take place on sand or stairs or other uneven surfaces, VERO has to prioritize not falling over before it decides how to do the collection. The final collecting maneuver is fine tuned using an extra Intel RealSense depth camera mounted on the robot’s chin.

VERO has been tested successfully in six different scenarios that challenge both its locomotion and detection capabilities.IIT

Initial testing with the robot in a variety of different environments showed that it could successfully collect just under 90 percent of cigarette butts, which I bet is better than I could do, and I’m also much more likely to get fed up with the whole process. The robot is not very quick at the task, but unlike me it will never get fed up as long as it’s got energy in its battery, so speed is somewhat less important.

As far as the authors of this paper are aware (and I assume they’ve done their research), this is “the first time that the legs of a legged robot are concurrently utilized for locomotion and for a different task.” This is distinct from other robots that can (for example) open doors with their feet, because those robots stop using the feet as feet for a while and instead use them as manipulators.

So, this is about a lot more than cigarette butts, and the researchers suggest a variety of other potential use cases, including spraying weeds in crop fields, inspecting cracks in infrastructure, and placing nails and rivets during construction.

Some use cases include potentially doing multiple things at the same time, like planting different kinds of seeds, using different surface sensors, or driving both nails and rivets. And since quadrupeds have four feet, they could potentially host four completely different tools, and the software that the researchers developed for VERO can be slightly modified to put whatever foot you want on whatever spot you need.

VERO: A vacuum‐cleaner‐equipped quadruped robot for efficient litter removal, by Lorenzo Amatucci, Giulio Turrisi, Angelo Bratta, Victor Barasuol, and Claudio Semini from IIT, was published in the Journal of Field Robotics.


Scientists in China have built what they claim to be the smallest and lightest solar-powered aerial vehicle. It’s small enough to sit in the palm of a person’s hand, weighs less than a U.S. nickel, and can fly indefinitely while the sun shines on it.

Micro aerial vehicles (MAVs) are insect- and bird-size aircraft that might prove useful for reconnaissance and other possible applications. However, a major problem that MAVs currently face is their limited flight times, usually about 30 minutes. Ultralight MAVs—those weighing less than 10 grams—can often only stay aloft for less than 10 minutes.

One potential way to keep MAVs flying longer is to power them with a consistent source of energy such as sunlight. Now, in a new study, researchers have developed what they say is the first solar-powered MAV capable of sustained flight.

The new ultralight MAV, CoulombFly, is just 4.21g with a wingspan of 20 centimeters. That’s about 10 times as small as and roughly 600 times as light as the previous smallest sunlight-powered aircraft, a quadcopter that’s 2 meters wide and weighs 2.6 kilograms.

Sunlight powered flight test Nature

“My ultimate goal is to make a super tiny flying vehicle, about the size and weight of a mosquito, with a wingspan under 1 centimeter,” says Mingjing Qi, a professor of energy and power engineering at Beihang University in Beijing. Qi and the scientists who built CoulombFly developed a prototype of such an aircraft, measuring 8 millimeters wide and 9 milligrams in mass, “but it can’t fly on its own power yet. I believe that with the ongoing development of microcircuit technology, we can make this happen.”

Previous sunlight-powered aerial vehicles typically rely on electromagnetic motors, which use electromagnets to generate motion. However, the smaller a solar-powered aircraft gets, the less surface area it has with which to collect sunlight, reducing the amount of energy it can generate. In addition, the efficiency of electromagnetic motors decrease sharply as vehicles shrink in size. Smaller electromagnetic motors experience comparably greater friction than larger ones, as well as greater energy losses due to electrical resistance from their components. This results in low lift-to-power efficiencies, Qi and his colleagues explain.

CoulombFly instead employs an electrostatic motor, which produce motion using electrostatic fields. Electrostatic motors are generally used as sensors in microelectromechanical systems (MEMS), not for aerial propulsion. Nevertheless, with a mass of only 1.52 grams, the electrostatic motor the scientists used has a lift-to-power efficiency two to three times that of other MAV motors.

The electrostatic motor has two nested rings. The inner ring is a spinning rotor that possesses 64 slats, each made of a carbon fiber sheet covered with aluminum foil. It resembles a wooden fence curved into a circle, with gaps between the fence’s posts. The outer ring is equipped eight alternating pairs of positive and negative electrode plates, which are each also made of a carbon fiber sheet bonded to aluminum foil. Each plate’s edge also possesses a brush made of aluminum that touches the inner ring’s slats.

Above CoulombFly’s electrostatic motor is a propeller 20 cm wide and connected to the rotor. Below the motor are two high-power-density thin-film gallium arsenide solar cells, each 4 by 6 cm in size, with a mass of 0.48 g and an energy conversion efficiency of more than 30 percent.

Sunlight electrically charges CoulombFly’s outer ring, and its 16 plates generate electric fields. The brushes on the outer ring’s plates touch the inner ring, electrically charging the rotor slats. The electric fields of the outer ring’s plates exert force on the charged rotor slats, making the inner ring and the propeller spin.

In tests under natural sunlight conditions—about 920 watts of light per square meter—CoulombFly successfully took off within one second and sustained flight for an hour without any deterioration in performance. Potential applications for sunlight-powered MAVs may include long-distance and long-duration aerial reconnaissance, the researchers say.

Long term test for hovering operation Nature

CoulombFly’s propulsion system can generate up to 5.8 g of lift. This means it could support an extra payload of roughly 1.59 g, which is “sufficient to accommodate the smallest available sensors, controllers, cameras and so on” to support future autonomous operations, Qi says. ”Right now, there’s still a lot of room to improve things like motors, propellers, and circuits, so we think we can get the extra payload up to 4 grams in the future. If we need even more payload, we could switch to quadcopters or fixed-wing designs, which can carry up to 30 grams.”

Qi adds “it should be possible for the vehicle to carry a tiny lithium-ion battery.” That means it could store energy from its solar panels and fly even when the sun is not out, potentially enabling 24-hour operations.

In the future, “we plan to use this propulsion system in different types of flying vehicles, like fixed-wing and rotorcraft,” Qi says.

The scientists detailed their findings online 17 July in the journal Nature.



Among the many things that humans cannot do (without some fairly substantial modification) is shifting our body morphology around on demand. It sounds a little extreme to be talking about things like self-amputation, and it is a little extreme, but it’s also not at all uncommon for other animals to do—lizards can disconnect their tails to escape a predator, for example. And it works in the other direction, too, with animals like ants adding to their morphology by connecting to each other to traverse gaps that a single ant couldn’t cross alone.

In a new paper, roboticists from The Faboratory at Yale University have given a soft robot the ability to detach and reattach pieces of itself, editing its body morphology when necessary. It’s a little freaky to watch, but it kind of makes me wish I could do the same thing.

Faboratory at Yale

These are fairly standard soft-bodied silicon robots that use asymmetrically stiff air chambers that inflate and deflate (using a tethered pump and valves) to generate a walking or crawling motion. What’s new here are the joints, which rely on a new material called a bicontinuous thermoplastic foam (BTF) to form a supportive structure for a sticky polymer that’s solid at room temperature but can be easily melted.

The BTF acts like a sponge to prevent the polymer from running out all over the place when it melts, and means that you can pull two BTF surfaces apart by melting the joint, and stick them together again by reversing the procedure. The process takes about 10 minutes and the resulting joint is quite strong. It’s also good for a couple hundred dettach/reattach cycles before degrading. It even stands up to dirt and water reasonably well.

Faboratory at Yale

This kind of thing has been done before with mechanical connections and magnets and other things like that—getting robots to attach to and detach from other robots is a foundational technique for modular robotics, after all. But these systems are inherently rigid, which is bad for soft robots, whose whole thing is about not being rigid. It’s all very preliminary, of course, because there are plenty of rigid things attached to these robots with tubes and wires and stuff. And there’s no autonomy or payloads here either. That’s not the point, though—the point is the joint, which (as the researchers point out) is “the first instantiation of a fully soft reversible joint” resulting in the “potential for soft artificial systems [that can] shape change via mass addition and subtraction.”

Self-Amputating and Interfusing Machines, by Bilige Yang, Amir Mohammadi Nasab, Stephanie J. Woodman, Eugene Thomas, Liana G. Tilton, Michael Levin, and Rebecca Kramer-Bottiglio from Yale, was published in May in Advanced Materials.

.



Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.

RoboCup 2024: 17–22 July 2024, EINDHOVEN, NETHERLANDSICRA@40: 23–26 September 2024, ROTTERDAM, NETHERLANDSIROS 2024: 14–18 October 2024, ABU DHABI, UAEICSR 2024: 23–26 October 2024, ODENSE, DENMARKCybathlon 2024: 25–27 October 2024, ZURICH

Enjoy today’s videos!

At ICRA 2024, Spectrum editor Evan Ackerman sat down with Unitree Founder and CEO Xingxing Wang and Tony Yang, VP of Business Development, to talk about the company’s newest humanoid, the G1 model.

[ Unitree ]

SACRIFICE YOUR BODY FOR THE ROBOT

[ WVUIRL ]

From navigating uneven terrain outside the lab to pure vision perception, GR-1 continues to push the boundaries of what’s possible.

[ Fourier ]

Aerial manipulation has gained interest for completing high-altitude tasks that are challenging for human workers, such as contact inspection and defect detection. This letter addresses a more general and dynamic task: simultaneously tracking time-varying contact force and motion trajectories on tangential surfaces. We demonstrate the approach on an aerial calligraphy task using a novel sponge pen design as the end-effector.

[ CMU ]

LimX Dynamics Biped Robot P1 was kicked and hit: Faced with random impacts in a crowd, P1 with its new design once again showcased exceptional stability as a mobility platform.

[ LimX Dynamics ]

Thanks, Ou Yan!

This is from ICRA 2018, but it holds up pretty well in the novelty department.

[ SNU INRoL ]

I think someone needs to crank the humor setting up on this one.

[ Deep Robotics ]

The paper summarizes the work at the Micro Air Vehicle Laboratory on end-to-end neural control of quadcopters. A major challenge in bringing these controllers to life is the “reality gap” between the real platform and the training environment. To address this, we combine online identification of the reality gap with pre-trained corrections through a deep neural controller, which is orders of magnitude more efficient than traditional computation of the optimal solution.

[ MAVLab ]

This is a dedicated Track Actuator from HEBI Robotics. Why they didn’t just call it a “tracktuator” is beyond me.

[ HEBI Robotics ]

Menteebot can navigate complex environments by combining a 3D model of the world with a dynamic obstacle map. On the first day in a new location, Menteebot generates the 3D model by following a person who shows the robot around.

[ Mentee Robotics ]

Here’s that drone with a 68kg payload and 70km range you’ve always wanted.

[ Malloy ]

AMBIDEX is a dual-armed robot with an innovative mechanism developed for safe coexistence with humans. Based on an innovative cable structure, it is designed to be both strong and stable.

[ NAVER Labs ]

As quadrotors take on an increasingly diverse range of roles, researchers often need to develop new hardware platforms tailored for specific tasks, introducing significant engineering overhead. In this article, we introduce the UniQuad series, a unified and versatile quadrotor hardware platform series that offers high flexibility to adapt to a wide range of common tasks, excellent customizability for advanced demands, and easy maintenance in case of crashes.

[ HKUST ]

The video demonstrates the field testing of a 43 kg (95 lb) amphibious cycloidal propeller unmanned underwater vehicle (Cyclo-UUV) developed at the Advanced Vertical Flight Laboratory, Texas A&M University. The vehicle utilizes a combination of cycloidal propellers (or cyclo-propellers), screw propellers, and tank treads for operations on land and underwater.

[ TAMU ]

The “pill” (the package hook) on Wing’s delivery drones is a crucial component to our aircraft! Did you know our package hook is designed to be aerodynamic and has stable flight characteristics, even at 65 mph?

[ Wing ]

Happy 50th to robotics at ABB!

[ ABB ]

This JHU Center for Functional Anatomy & Evolution Seminar is by Chen Li, on Terradynamics of Animals & Robots in Complex Terrain.

[ JHU ]



Food prep is one of those problems that seems like it should be solvable by robots. It’s a predictable, repetitive, basic manipulation task in a semi-structured environment—seems ideal, right? And obviously there’s a huge need, because human labor is expensive and getting harder and harder to find in these contexts. There are currently over a million unfilled jobs in the food industry in the United States, and even with jobs that are filled, the annual turnover rate is 150 percent (meaning a lot of workers don’t even last a year).

Food prep seems like a great opportunity for robots, which is why Chef Robotics and a handful of other robotics companies tackled it a couple years ago by bringing robots to fast casual restaurants like Chipotle or Sweetgreen, where you get served a custom-ish meal from a selection of ingredients at a counter.

But this didn’t really work out, for a couple of reasons. First, doing things that are mostly effortless for humans are inevitably extremely difficult for robots. And second, humans actually do a lot of useful things in a restaurant context besides just putting food onto plates, and the robots weren’t up for all of those things.

Still, Chef Robotics founder and CEO Rajat Bhageria wasn’t ready to let this opportunity go. “The food market is arguably the biggest market that’s tractable for AI today,” he told IEEE Spectrum. And with a bit of a pivot away from the complicated mess of fast casual restaurants, Chef Robotics has still managed to prepare over 20 million meals thanks to autonomous robot arms deployed all over North America. Without knowing it, you may even have eaten such a meal.

“The hard thing is, can you pick fast? Can you pick consistently? Can you pick the right portion size without spilling? And can you pick without making it look like the food was picked by a machine?” —Rajat Bhageria, Chef Robotics

When we spoke with Bhageria, he explained that there are three basic tasks involved in prepared food production: prep (tasks like chopping ingredients), the actual cooking process, and then assembly (or plating). Of these tasks, prep scales pretty well with industrial automation in that you can usually order pre-chopped or mixed ingredients, and cooking also scales well since you can cook more with only a minimal increase in effort just by using a bigger pot or pan or oven. What doesn’t scale well is the assembly, especially when any kind of flexibility or variety is required. You can clearly see this in action at any fast casual restaurant, where a couple of people are in the kitchen cooking up massive amounts of food while each customer gets served one at a time.

So with that bottleneck identified, let’s throw some robots at the problem, right? And that’s exactly what Chef Robotics did, explains Bhageria: “we went to our customers, who said that their biggest pain point was labor, and the most labor is in assembly, so we said, we can help you solve this.”

Chef Robotics started with fast casual restaurants. They weren’t the first to try this—many other robotics companies had attempted this before, with decidedly mixed results. “We actually had some good success in the early days selling to fast casual chains,” Bhageria says, “but then we had some technical obstacles. Essentially, if we want to have a human-equivalent system so that we can charge a human-equivalent service fee for our robot, we need to be able to do every ingredient. You’re either a full human equivalent, or our customers told us it wouldn’t be useful.”

Part of the challenge is that training robots do perform all of the different manipulations required for different assembly tasks requires different kinds of real world data. That data simply doesn’t exist—or, if it does, any company that has it knows what it’s worth and isn’t sharing. You can’t easily simulate this kind of data, because food can be gross and difficult to handle, whether it’s gloopy or gloppy or squishy or slimy or unpredictably deformable in some other way, and you really need physical experience to train a useful manipulation model.

Setting fast casual restaurants aside for a moment, what about food prep situations where things are as predictable as possible, like mass-produced meals? We’re talking about food like frozen dinners, that have a handful of discrete ingredients packed into trays at factory scale. Frozen meal production relies on automation rather than robotics because the scale is such that the cost of dedicated equipment can be justified.

There’s a middle ground, though, where robots have found (some) opportunity: When you need to produce a high volume of the same meal, but that meal changes regularly. For example, think of any kind of pre-packaged meal that’s made in bulk, just not at frozen-food scale. It’s an opportunity for automation in a structured environment—but with enough variety that actual automation isn’t cost effective. Suddenly, robots and their tiny bit of flexible automation have a chance to be a practical solution.

“We saw these long assembly lines, where humans were scooping food out of big tubs and onto individual trays,” Bhageria says. “They do a lot of different meals on these lines; it’s going to change over and they’re going to do different meals throughout the week. But at any given moment, each person is doing one ingredient, and maybe on a weekly basis, that person would do six ingredients. This was really compelling for us because six ingredients is something we can bootstrap in a lab. We can get something good enough and if we can get something good enough, then we can ship a robot, and if we can ship a robot to production, then we will get real world training data.”

Chef Robotics has been deploying robot modules that they can slot into existing food assembly lines in place of humans without any retrofitting necessary. The modules consist of six degree of freedom arms wearing swanky IP67 washable suits. To handle different kinds of food, the robots can be equipped with a variety of different utensils (and their accompanying manipulation software strategies). Sensing includes a few depth cameras, as well as a weight-sensing platform for the food tray to ensure consistent amounts of food are picked. And while arms with six degrees of freedom may be overkill for now, eventually the hope is that they’ll be able to handle more complex food like asparagus, where you need to do a little bit more than just scoop.

While Chef Robotics seems to have a viable business here, Bhageria tells us that he keeps coming back to that vision of robots being useful in fast casual restaurants, and eventually, robots making us food in our homes. Making that happen will require time, experience, technical expertise, and an astonishing amount of real-world training data, which is the real value behind those 20 million robot-prepared meals (and counting). The more robots the company deploys, the more data they collect, which will allow them to train their food manipulation models to handle a wider variety of ingredients to open up even more deployments. Their robots, Chef’s website says, “essentially act as data ingestion engines to improve our AI models.”

The next step is likely ghost kitchens where the environment is still somewhat controlled and human interaction isn’t necessary, followed by deployments in commercial kitchens more broadly. But even that won’t be enough for Bhageria, who wants robots that can take over from all of the drudgery in food service: “I’m really excited about this vision,” he says. “How do we deploy hundreds of millions of robots all over the world that allow humans to do what humans do best?”



Against all odds, Ukraine is still standing almost two and a half years after Russia’s massive 2022 invasion. Of course, hundreds of billions of dollars in Western support as well as Russian errors have helped immensely, but it would be a mistake to overlook Ukraine’s creative use of new technologies, particularly drones. While uncrewed aerial vehicles have grabbed most of the attention, it is naval drones that could be the key to bringing Russian president Vladimir Putin to the negotiating table.

These naval-drone operations in the Black Sea against Russian warships and other targets have been so successful that they are prompting, in London, Paris, Washington, and elsewhere, fundamental reevaluations of how drones will affect future naval operations. In August, 2023, for example, the Pentagon launched the billion-dollar Replicator initiative to field air and naval drones (also called sea drones) on a massive scale. It’s widely believed that such drones could be used to help counter a Chinese invasion of Taiwan.

And yet Ukraine’s naval drones initiative grew out of necessity, not grand strategy. Early in the war, Russia’s Black Sea fleet launched cruise missiles into Ukraine and blockaded Odesa, effectively shutting down Ukraine’s exports of grain, metals, and manufactured goods. The missile strikes terrorized Ukrainian citizens and shut down the power grid, but Russia’s blockade was arguably more consequential, devastating Ukraine’s economy and creating food shortages from North Africa to the Middle East.

With its navy seized or sunk during the war’s opening days, Ukraine had few options to regain access to the sea. So Kyiv’s troops got creative. Lukashevich Ivan Volodymyrovych, a brigadier general in the Security Service of Ukraine, the country’s counterintelligence agency, proposed building a series of fast, uncrewed attack boats. In the summer of 2022, the service, which is known by the acronym SBU, began with a few prototype drones. These quickly led to a pair of naval drones that, when used with commercial satellite imagery, off-the-shelf uncrewed aircraft, and Starlink terminals, gave Ukrainian operators the means to sink or disable a third of Russia’s Black Sea Fleet, including the flagship Moskva and most of the fleet’s cruise-missile-equipped warships.

To protect their remaining vessels, Russian commanders relocated the Black Sea Fleet to Novorossiysk, 300 kilometers east of Crimea. This move sheltered the ships from Ukrainian drones and missiles, but it also put them too far away to threaten Ukrainian shipping or defend the Crimean Peninsula. Kyiv has exploited the opening by restoring trade routes and mounting sustained airborne and naval drone strikes against Russian bases on Crimea and the Kerch Strait Bridge connecting the peninsula with Russia.

How Maguras and Sea Babies Hunt and Attack

The first Ukrainian drone boats were cobbled together with parts from jet skis, motorboats, and off-the-shelf electronics. But within months, manufacturers working for the Ukraine defense ministry and SBU fielded several designs that proved their worth in combat, most notably the Magura V5 and the Sea Baby.

Carrying a 300-kilogram warhead, on par with that of a heavyweight torpedo, the Magura V5 is a hunter-killer antiship drone designed to work in swarms that confuse and overwhelm a ship’s defenses. Equipped with Starlink terminals, which connect to SpaceX’s Starlink satellites, and GPS, a group of about three to five Maguras likely moves autonomously to a location near the potential target. From there, operators can wait until conditions are right and then attack the target from multiple angles using remote control and video feeds from the vehicles.

A Ukrainian Magura V5 hunter-killer sea drone was demonstrated at an undisclosed location in Ukraine on 13 April 2024. The domed pod toward the bow, which can rotate from side to side, contains a thermal camera used for guidance and targeting.Valentyn Origrenko/Reuters/Redux

Larger than a Magura, the Sea Baby is a multipurpose vehicle that can carry about 800 kg of explosives, which is close to twice the payload of a Tomahawk cruise missile. A Sea Baby was used in 2023 to inflict substantial damage to the Kerch Strait Bridge. A more recent version carries a rocket launcher that Ukraine troops plan to use against Russian forces along the Dnipro River, which flows through eastern Ukraine and has often formed the frontline in that part of the country. Like a Magura, a Sea Baby is likely remotely controlled using Starlink and GPS. In addition to attack, it’s also equipped for surveillance and logistics.

Russia reduced the threat to its ships by moving them out of the region, but fixed targets like the Kerch Strait Bridge remain vulnerable to Ukrainian sea drones. To try to protect these structures from drone onslaughts, Russian commanders are taking a “kitchen sink” approach, submerging hulks around bridge supports, fielding more guns to shoot at incoming uncrewed vessels, and jamming GPS and Starlink around the Kerch Strait.

Ukrainian service members demonstrated the portable, ruggedized consoles used to remotely guide the Magura V5 naval drones in April 2024.Valentyn Origrenko/Reuters/Redux

While the war remains largely stalemated in the country’s north, Ukraine’s naval drones could yet force Russia into negotiations. The Crimean Peninsula was Moscow’s biggest prize from its decade-long assault on Ukraine. If the Kerch Bridge is severed and the Black Sea Fleet pushed back into Russian ports, Putin may need to end the fighting to regain control over Crimea.

Why the U.S. Navy Embraced the Swarm

Ukraine’s small, low-cost sea drones are offering a compelling view of future tactics and capabilities. But recent experiences elsewhere in the world are highlighting the limitations of drones for some crucial tasks. For example, for protecting shipping from piracy or stopping trafficking and illegal fishing, drones are less useful.

Before the Ukraine war, efforts by the U.S. Department of Defense to field surface sea drones focused mostly on large vehicles. In 2015, the Defense Advanced Research Projects Agency started, and the U.S. Navy later continued, a project that built two uncrewed surface vessels, called Sea Hunter and Sea Hawk. These were 130-tonne sea drones capable of roaming the oceans for up to 70 days while carrying payloads of thousands of pounds each. The point was to demonstrate the ability to detect, follow, and destroy submarines. The Navy and the Pentagon’s secretive Strategic Capabilities Office followed with the Ghost Fleet Overlord uncrewed vessel programs, which produced four larger prototypes designed to carry shipping-container-size payloads of missiles, sensors, or electronic countermeasures.

The U.S. Navy’s newly created Uncrewed Surface Vessel Division 1 ( USVDIV-1) completed a deployment across the Pacific Ocean last year with four medium and large sea drones: Sea Hunter and Sea Hawk and two Overlord vessels, Ranger and Mariner. The five-month deployment from Port Hueneme, Calif., took the vessels to Hawaii, Japan, and Australia, where they joined in annual exercises conducted by U.S. and allied navies. The U.S. Navy continues to assess its drone fleet through sea trials lasting from several days to a few months.

The Sea Hawk is a U.S. Navy trimaran drone vessel designed to find, pursue, and attack submarines. The 130-tonne ship, photographed here in October of 2023 in Sydney Harbor, was built to operate autonomously on missions of up to 70 days, but it can also accommodate human observers on board. Ensign Pierson Hawkins/U.S. Navy

In contrast with Ukraine’s small sea drones, which are usually remotely controlled and operate outside shipping lanes, the U.S. Navy’s much larger uncrewed vessels have to follow the nautical rules of the road. To navigate autonomously, these big ships rely on robust onboard sensors, processing for computer vision and target-motion analysis, and automation based on predictable forms of artificial intelligence, such as expert- or agent-based algorithms rather than deep learning.

But thanks to the success of the Ukrainian drones, the focus and energy in sea drones are rapidly moving to the smaller end of the scale. The U.S. Navy initially envisioned platforms like Sea Hunter conducting missions in submarine tracking, electronic deception, or clandestine surveillance far out at sea. And large drones will still be needed for such missions. However, with the right tactics and support, a group of small sea drones can conduct similar missions as well as other vital tasks.

For example, though they are constrained in speed, maneuverability, and power generation, solar- or sail-powered drones can stay out for months with little human intervention. The earliest of these are wave gliders like the Liquid Robotics (a Boeing company) SHARC, which has been conducting undersea and surface surveillance for the U.S. Navy for more than a decade. Newer designs like the Saildrone Voyager and Ocius Blue Bottle incorporate motors and additional solar or diesel power to haul payloads such as radars, jammers, decoys, or active sonars. The Ocean Aero Triton takes this model one step further: It can submerge, to conduct clandestine surveillance or a surprise attack, or to avoid detection.

The Triton, from Ocean Aero in Gulfport, Miss., is billed as the world’s only autonomous sea drone capable of both cruising underwater and sailing on the surface. Ocean Aero

Ukraine’s success in the Black Sea has also unleashed a flurry of new small antiship attack drones. USVDIV-1 will use the GARC from Maritime Applied Physics Corp. to develop tactics. The Pentagon’s Defense Innovation Unit has also begun purchasing drones for the China-focused Replicator initiative. Among the likely craft being evaluated are fast-attack sea drones from Austin, Texas–based Saronic.

Behind the soaring interest in small and inexpensive sea drones is the changing value proposition for naval drones. As recently as four years ago, military planners were focused on using them to replace crewed ships in “dull, dirty, and dangerous” jobs. But now, the thinking goes, sea drones can provide scale, adaptability, and resilience across each link in the “kill chain” that extends from detecting a target to hitting it with a weapon.

Today, to attack a ship, most navies generally have one preferred sensor (such as a radar system), one launcher, and one missile. But what these planners are now coming to appreciate is that a fleet of crewed surface ships with a collection of a dozen or two naval drones would offer multiple paths to both find that ship and attack it. These craft would also be less vulnerable, because of their dispersion.

Defending Taiwan by Surrounding It With a “Hellscape”

U.S. efforts to protect Taiwan may soon reflect this new value proposition. Many classified and unclassified war games suggest Taiwan and its allies could successfully defend the island—but at costs high enough to potentially dissuade a U.S. president from intervening on Taiwan’s behalf. With U.S. defense budgets capped by law and procurement constrained by rising personnel and maintenance costs, substantially growing or improving today’s U.S. military for this specific purpose is unrealistic. Instead, commanders are looking for creative solutions to slow or stop a Chinese invasion without losing most U.S. forces in the process.

Naval drones look like a good—and maybe the best— solution. The Taiwan Strait is only 160 kilometers (100 miles) wide, and Taiwan’s coastline offers only a few areas where large numbers of troops could come ashore. U.S. naval attack drones positioned on the likely routes could disrupt or possibly even halt a Chinese invasion, much as Ukrainian sea drones have denied Russia access to the western Black Sea and, for that matter, Houthi-controlled drones have sporadically closed off large parts of the Red Sea in the Middle East.

Rather than killer robots seeking out and destroying targets, the drones defending Taiwan would be passively waiting for Chinese forces to illegally enter a protected zone, within which they could be attacked.

The new U.S. Indo-Pacific Command leader, Admiral Sam Paparo, wants to apply this approach to defending Taiwan in a scenario he calls “Hellscape.” In it, U.S. surface and undersea drones would likely be based near Taiwan, perhaps in the Philippines or Japan. When the potential for an invasion rises, the drones would move themselves or be carried by larger uncrewed or crewed ships to the western coast of Taiwan to wait.

Sea drones are well-suited to this role, thanks in part to the evolution of naval technologies and tactics over the past half century. Until World War II, submarines were the most lethal threat to ships. But since the Cold War, long-range subsonic, supersonic, and now hypersonic antiship missiles have commanded navy leaders’ attention. They’ve spent decades devising ways to protect their ships against such antiship missiles.

Much less effort has gone into defending against torpedoes, mines—or sea drones. A dozen or more missiles might be needed to ensure that just one reaches a targeted ship, and even then, the damage may not be catastrophic. But a single surface or undersea drone could easily evade detection and explode at a ship’s waterline to sink it, because in this case, water pressure does most of the work.

The level of autonomy available in most sea drones today is more than enough to attack ships in the Taiwan Strait. Details of U.S. military plans are classified, but a recent Hudson Institute report that I wrote with Dan Patt, proposes a possible approach. In it, a drone flotilla, consisting of about three dozen hunter-killer surface drones, two dozen uncrewed surface vessels carrying aerial drones, and three dozen autonomous undersea drones, would take up designated positions in a “kill box” adjacent to one of Taiwan’s western beaches if a Chinese invasion fleet had begun massing on the opposite side of the strait. Even if they were based in Japan or the Philippines, the drones could reach Taiwan within a day. Upon receiving a signal from operators remotely using Starlink or locally using a line-of-sight radio, the drones would act as a mobile minefield, attacking troop transports and their escorts inside Taiwan’s territorial waters. Widely available electro-optical and infrared sensors, coupled to recognition algorithms, would direct the drones to targets.

Although communications with operators onshore would likely be jammed, the drones could coordinate their actions locally using line-of-sight Internet Protocol–based networks like Silvus or TTNT. For example, surface vessels could launch aerial drones that would attack the pilot houses and radars of ships, while surface and undersea drones strike ships at the waterline. The drones could also coordinate to ensure they do not all strike the same target and to prioritize the largest targets first. These kinds of simple collaborations are routine in today’s drones.

Treating drones like mines reduces the complexity needed in their control systems and helps them comply with Pentagon rules for autonomous weapons. Rather than killer robots seeking out and destroying targets, the drones defending Taiwan would be passively waiting for Chinese forces to illegally enter a protected zone, within which they could be attacked.

Like Russia’s Black Sea Fleet, the Chinese navy will develop countermeasures to sea drones, such as employing decoy ships, attacking drones from the air, or using minesweepers to move them away from the invasion fleet. To stay ahead, operators will need to continue innovating tactics and behaviors through frequent exercises and experiments, like those underway at U.S. Navy Unmanned Surface Vessel Squadron Three. (Like the USVDIV-1, it is a unit under the U.S. Navy’s Surface Development Squadron One.) Lessons from such exercises would be incorporated into the defending drones as part of their programming before a mission.

The emergence of sea drones heralds a new era in naval warfare. After decades of focusing on increasingly lethal antiship missiles, navies now have to defend against capable and widely proliferating threats on, above, and below the water. And while sea drone swarms may be mainly a concern for coastal areas, these choke points are critical to the global economy and most nations’ security. For U.S. and allied fleets, especially, naval drones are a classic combination of threat and opportunity. As the Hellscape concept suggests, uncrewed vessels may be a solution to some of the most challenging and sweeping of modern naval scenarios for the Pentagon and its allies—and their adversaries.

This article was updated on 10 July 2024. An earlier version stated that sea drones from Saronic Technologies are being purchased by the U.S. Department of Defense’s Defense Innovation Unit. This could not be publicly confirmed.



Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.

RoboCup 2024: 17–22 July 2024, EINDHOVEN, NETHERLANDSICRA@40: 23–26 September 2024, ROTTERDAM, NETHERLANDSIROS 2024: 14–18 October 2024, ABU DHABI, UAEICSR 2024: 23–26 October 2024, ODENSE, DENMARKCybathlon 2024: 25–27 October 2024, ZURICH

Enjoy today’s videos!

Figure is making progress toward a humanoid robot that can do something useful, but keep in mind that the “full use case” here is not one continuous shot.

[ Figure ]

Can this robot survive a 1-meter drop? Spoiler alert: it cannot.

[ WVUIRL ]

One of those things that’s a lot harder for robots than it probably looks.

This is a demo of hammering a nail. The instantaneous rebound force from the hammer is absorbed through a combination of the elasticity of the rubber material securing the hammer, the deflection in torque sensors and harmonic gears, back-drivability, and impedance control. This allows the nail to be driven with a certain amount of force.

[ Tokyo Robotics ]

Although bin packing has been a key benchmark task for robotic manipulation, the community has mainly focused on the placement of rigid rectilinear objects within the container. We address this by presenting a soft robotic hand that combines vision, motor-based proprioception, and soft tactile sensors to identify, sort, and pack a stream of unknown objects.

[ MIT CSAIL ]

Status Update: Extending traditional visual servo and compliant control by integrating the latest reinforcement and imitation learning control methodologies, UBTECH gradually trains the embodied intelligence-based “cerebellum” of its humanoid robot Walker S for diverse industrial manipulation tasks.

[ UBTECH ]

If you’re gonna ask a robot to stack bread, better make it flat.

[ FANUC ]

Cassie has to be one of the most distinctive sounding legged robots there is.

[ Paper ]

Twice the robots are by definition twice as capable, right...?

[ Pollen Robotics ]

The Robotic Systems Lab participated in the Advanced Industrial Robotic Applications (AIRA) Challenge at the ACHEMA 2024 process industry trade show, where teams demonstrated their teleoperated robotic solutions for industrial inspection tasks. We competed with the ALMA legged manipulator robot, teleoperated using a second robot arm in a leader-follower configuration, placing us in third place for the competition.

[ ETHZ RSL ]

This is apparently “peak demand” in a single market for Wing delivery drones.

[ Wing ]

Using a new type of surgical intervention and neuroprosthetic interface, MIT researchers, in collaboration with colleagues from Brigham and Women’s Hospital, have shown that a natural walking gait is achievable using a prosthetic leg fully driven by the body’s own nervous system. The surgical amputation procedure reconnects muscles in the residual limb, which allows patients to receive “proprioceptive” feedback about where their prosthetic limb is in space.

[ MIT ]

Coal mining in Forest of Dean (UK) is such a difficult and challenging job. Going into the mine as human is sometimes almost impossible. We did it with our robot while inspecting the mine with our partners (Forestry England) and the local miners!

[ UCL RPL ]

Chill.

[ ABB ]

Would you tango with a robot? Inviting us into the fascinating world of dancing machines, robot choreographer Catie Cuan highlights why teaching robots to move with grace, intention and emotion is essential to creating AI-powered machines we will want to welcome into our daily lives.

[ TED ]



It may at times seem like there are as many humanoid robotics companies out there as the industry could possibly sustain, but the potential for useful and reliable and affordable humanoids is so huge that there’s plenty of room for any company that can actually get them to work. Joining the dozen or so companies already on this quest is Persona AI, founded last month by Nic Radford and Jerry Pratt, two people who know better than just about anyone what it takes to make a successful robotics company, although they also know enough to be wary of getting into commercial humanoids.


Persona AI may not be the first humanoid robotics startup, but its founders have some serious experience in the space:

Nic Radford lead the team that developed NASA’s Valkyrie humanoid robot, before founding Houston Mechatronics (now Nauticus Robotics), which introduced a transforming underwater robot in 2019. He also founded Jacobi Motors, which is commercializing variable flux electric motors.

Jerry Pratt worked on walking robots for 20 years at the Institute for Human and Machine Cognition (IHMC) in Pensacola, Florida. He co-founded Boardwalk Robotics in 2017, and has spent the last two years as CTO of multi-billion-dollar humanoid startup Figure.

“It took me a long time to warm up to this idea,” Nic Radford tells us. “After I left Nauticus in January, I didn’t want anything to do with humanoids, especially underwater humanoids, and I didn’t even want to hear the word ‘robot.’ But things are changing so quickly, and I got excited and called Jerry and I’m like, this is actually very possible.” Jerry Pratt, who recently left Figure due primarily to the two-body problem, seems to be coming from a similar place: “There’s a lot of bashing your head against the wall in robotics, and persistence is so important. Nic and I have both gone through pessimism phases with our robots over the years. We’re a bit more optimistic about the commercial aspects now, but we want to be pragmatic and realistic about things too.”

Behind all of the recent humanoid hype lies the very, very difficult problem of making a highly technical piece of hardware and software compete effectively with humans in the labor market. But that’s also a very, very big opportunity—big enough that Persona doesn’t have to be the first company in this space, or the best funded, or the highest profile. They simply have to succeed, but of course sustainable commercial success with any robot (and bipedal robots in particular) is anything but simple. Step one will be building a founding team across two locations: Houston and Pensacola, Fla. But Radford says that the response so far to just a couple of LinkedIn posts about Persona has been “tremendous.” And with a substantial seed investment in the works, Persona will have more than just a vision to attract top talent.

For more details about Persona, we spoke with Persona AI co-founders Nic Radford and Jerry Pratt.

Why start this company, why now, and why you?

Nic Radford

Nic Radford: The idea for this started a long time ago. Jerry and I have been working together off and on for quite a while, being in this field and sharing a love for what the humanoid potential is while at the same time being frustrated by where humanoids are at. As far back as probably 2008, we were thinking about starting a humanoids company, but for one reason or another the viability just wasn’t there. We were both recently searching for our next venture and we couldn’t imagine sitting this out completely, so we’re finally going to explore it, although we know better than anyone that robots are really hard. They’re not that hard to build; but they’re hard to make useful and make money with, and the challenge for us is whether we can build a viable business with Persona: can we build a business that uses robots and makes money? That’s our singular focus. We’re pretty sure that this is likely the best time in history to execute on that potential.

Jerry Pratt: I’ve been interested in commercializing humanoids for quite a while—thinking about it, and giving it a go here and there, but until recently it has always been the wrong time from both a commercial point of view and a technological readiness point of view. You can think back to the DARPA Robotics Challenge days when we had to wait about 20 seconds to get a good lidar scan and process it, which made it really challenging to do things autonomously. But we’ve gotten much, much better at perception, and now, we can get a whole perception pipeline to run at the framerate of our sensors. That’s probably the main enabling technology that’s happened over the last 10 years.

From the commercial point of view, now that we’re showing that this stuff’s feasible, there’s been a lot more pull from the industry side. It’s like we’re at the next stage of the Industrial Revolution, where the harder problems that weren’t roboticized from the 60s until now can now be. And so, there’s really good opportunities in a lot of different use cases.

A bunch of companies have started within the last few years, and several were even earlier than that. Are you concerned that you’re too late?

Radford: The concern is that we’re still too early! There might only be one Figure out there that raises a billion dollars, but I don’t think that’s going to be the case. There’s going to be multiple winners here, and if the market is as large as people claim it is, you could see quite a diversification of classes of commercial humanoid robots.

Jerry Pratt

Pratt: We definitely have some catching up to do but we should be able to do that pretty quickly, and I’d say most people really aren’t that far from the starting line at this point. There’s still a lot to do, but all the technology is here now—we know what it takes to put together a really good team and to build robots. We’re also going to do what we can to increase speed, like by starting with a surrogate robot from someone else to get the autonomy team going while building our own robot in parallel.

Radford: I also believe that our capital structure is a big deal. We’re taking an anti-stealth approach, and we want to bring everyone along with us as our company grows and give out a significant chunk of the company to early joiners. It was an anxiety of ours that we would be perceived as a me-too and that nobody was going to care, but it’s been the exact opposite with a compelling response from both investors and early potential team members.

So your approach here is not to look at all of these other humanoid robotics companies and try and do something they’re not, but instead to pursue similar goals in a similar way in a market where there’s room for all?

Pratt: All robotics companies, and AI companies in general, are standing on the shoulders of giants. These are the thousands of robotics and AI researchers that have been collectively bashing their heads against the myriad problems for decades—some of the first humanoids were walking at Waseda University in the late 1960s. While there are some secret sauces that we might bring to the table, it is really the combined efforts of the research community that now enables commercialization.

So if you’re at a point where you need something new to be invented in order to get to applications, then you’re in trouble, because with invention you never know how long it’s going to take. What is available today and now, the technology that’s been developed by various communities over the last 50+ years—we all have what we need for the first three applications that are widely mentioned: warehousing, manufacturing, and logistics. The big question is, what’s the fourth application? And the fifth and the sixth? And if you can start detecting those and planning for them, you can get a leg up on everybody else.

The difficulty is in the execution and integration. It’s a ten thousand—no, that’s probably too small—it’s a hundred thousand piece puzzle where you gotta get each piece right, and occasionally you lose some pieces on the floor that you just can’t find. So you need a broad team that has expertise in like 30 different disciplines to try to solve the challenge of an end-to-end labor solution with humanoid robots.

Radford: The idea is like one percent of starting a company. The rest of it, and why companies fail, is in the execution. Things like, not understanding the market and the product-market fit, or not understanding how to run the company, the dimensions of the actual business. I believe we’re different because with our backgrounds and our experience we bring a very strong view on execution, and that is our focus on day one. There’s enough interest in the VC community that we can fund this company with a singular focus on commercializing humanoids for a couple different verticals.

But listen, we got some novel ideas in actuation and other tricks up our sleeve that might be very compelling for this, but we don’t want to emphasize that aspect. I don’t think Persona’s ultimate success comes just from the tech component. I think it comes mostly from ‘do we understand the customer, the market needs, the business model, and can we avoid the mistakes of the past?’

How is that going to change things about the way that you run Persona?

Radford: I started a company [Houston Mechatronics] with a bunch of research engineers. They don’t make the best product managers. More broadly, if you’re staffing all your disciplines with roboticists and engineers, you’ll learn that it may not be the most efficient way to bring something to market. Yes, we need those skills. They are essential. But there’s so many other aspects of a business that get overlooked when you’re fundamentally a research lab trying to commercialize a robot. I’ve been there, I’ve done that, and I’m not interested in making that mistake again.

Pratt: It’s important to get a really good product team that’s working with a customer from day one to have customer needs drive all the engineering. The other approach is ‘build it and they will come’ but then maybe you don’t build the right thing. Of course, we want to build multi-purpose robots, and we’re steering clear of saying ‘general purpose’ at this point. We don’t want to overfit to any one application, but if we can get to a dozen use cases, two or three per customer site, then we’ve got something.

There still seems to be a couple of unsolved technical challenges with humanoids, including hands, batteries, and safety. How will Persona tackle those things?

Pratt: Hands are such a hard thing—getting a hand that has the required degrees of freedom and is robust enough that if you accidentally hit it against your table, you’re not just going to break all your fingers. But we’ve seen robotic hand companies popping up now that are showing videos of hitting their hands with a hammer, so I’m hopeful.

Getting one to two hours of battery life is relatively achievable. Pushing up towards five hours is super hard. But batteries can now be charged in 20 minutes or so, as long as you’re going from 20 percent to 80 percent. So we’re going to need a cadence where robots are swapping in and out and charging as they go. And batteries will keep getting better.

Radford: We do have a focus on safety. It was paramount at NASA, and when we were working on Robonaut, it led to a lot of morphological considerations with padding. In fact, the first concepts and images we have of our robot illustrate extensive padding, but we have to do that carefully, because at the end of the day it’s mass and it’s inertia.

What does the near future look like for you?

Pratt: Building the team is really important—getting those first 10 to 20 people over the next few months. Then we’ll want to get some hardware and get going really quickly, maybe buying a couple of robot arms or something to get our behavior and learning pipelines going while in parallel starting our own robot design. From our experience, after getting a good team together and starting from a clean sheet, a new robot takes about a year to design and build. And then during that period we’ll be securing a customer or two or three.

Radford: We’re also working hard on some very high profile partnerships that could influence our early thinking dramatically. Like Jerry said earlier, it’s a massive 100,000 piece puzzle, and we’re working on the fundamentals: the people, the cash, and the customers.



This article is part of our exclusive IEEE Journal Watch series in partnership with IEEE Xplore.

One of the (many) great things about robots is that they don’t have to be constrained by how their biological counterparts do things. If you have a particular problem your robot needs to solve, you can get creative with extra sensors: many quadrupeds have side cameras and butt cameras for obstacle avoidance, and humanoids sometimes have chest cameras and knee cameras to help with navigation along with wrist cameras for manipulation. But how far can you take this? I have no idea, but it seems like we haven’t gotten to the end of things yet because now there’s a quadruped with cameras on the bottom of its feet.

Sensorized feet is not a new idea; it’s pretty common for quadrupedal robots to have some kind of foot-mounted force sensor to detect ground contact. Putting an actual camera down there is fairly novel, though, because it’s not at all obvious how you’d go about doing it. And the way that roboticists from the Southern University of Science and Technology in Shenzhen went about doing it is, indeed, not at all obvious.

Go1’s snazzy feetsies have soles made of transparent acrylic, with slightly flexible plastic structure supporting a 60 millimeter gap up to each camera (640x480 at 120 frames per second) with a quartet of LEDs to provide illumination. While it’s complicated looking, at 120 grams, it doesn’t weigh all that much, and costs only about $50 per foot ($42 of which is the camera). The whole thing is sealed to keep out dirt and water.

So why bother with all of this (presumably somewhat fragile) complexity? As we ask quadruped robots to do more useful things in more challenging environments, having more information about what exactly they’re stepping on and how their feet are interacting with the ground is going to be super helpful. Robots that rely only on proprioceptive sensing (sensing self-movement) are great and all, but when you start trying to move over complex surfaces like sand, it can be really helpful to have vision that explicitly shows how your robot is interacting with the surface that it’s stepping on. Preliminary results showed that Foot Vision enabled the Go1 using it to perceive the flow of sand or soil around its foot as it takes a step, which can be used to estimate slippage, the bane of ground-contacting robots.

The researchers acknowledge that their hardware could use a bit of robustifying, and they also want to try adding some tread patterns around the circumference of the foot, since that plexiglass window is pretty slippery. The overall idea is to make Foot Vision as useful as the much more common gripper-integrated vision systems for robotic manipulation, helping legged robots make better decisions about how to get where they need to go.

Foot Vision: A Vision-Based Multi-Functional Sensorized Foot for Quadruped Robots, by Guowei Shi, Chen Yao, Xin Liu, Yuntian Zhao, Zheng Zhu, and Zhenzhong Jia from Southern University of Science and Technology in Shenzhen, is accepted to the July 2024 issue of IEEE Robotics and Automation Letters

.



Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.

RoboCup 2024: 17–22 July 2024, EINDHOVEN, NETHERLANDSICRA@40: 23–26 September 2024, ROTTERDAM, NETHERLANDSIROS 2024: 14–18 October 2024, ABU DHABI, UAEICSR 2024: 23–26 October 2024, ODENSE, DENMARKCybathlon 2024: 25–27 October 2024, ZURICH

Enjoy today’s videos!

Agility has been working with GXO for a bit now, but the big news here (and it IS big news) is that Agility’s Digit robots at GXO now represent the first formal commercial deployment of humanoid robots.

[ GXO ]

GXO can’t seem to get enough humanoids, because they’re also starting some R&D with Apptronik.

[ GXO ]

In this paper, we introduce a full-stack system for humanoids to learn motion and autonomous skills from human data. Through shadowing, human operators can teleoperate humanoids to collect whole-body data for learning different tasks in the real world. Using the data collected, we then perform supervised behavior cloning to train skill policies using egocentric vision, allowing humanoids to complete different tasks autonomously by imitating human skills.

THAT FACE.

[ HumanPlus ]

Yeah these robots are impressive but it’s the sound effects that make it.

[ Deep Robotics ]

Meet CARMEN, short for Cognitively Assistive Robot for Motivation and Neurorehabilitation–a small, tabletop robot designed to help people with mild cognitive impairment (MCI) learn skills to improve memory, attention, and executive functioning at home.

[ CARMEN ] via [ UCSD ]

Thanks, Ioana!

The caption of this video is, “it did not work...”

You had one job, e-stop person! ONE JOB!

[ WVUIRL ]

This is a demo of cutting wood with a saw. When using position control for this task, precise measurement of the cutting amount is necessary. However, by using impedance control, this requirement is eliminated, allowing for successful cutting with only rough commands.

[ Tokyo Robotics ]

This is mesmerizing.

[ Oregon State ]

Quadrupeds are really starting to look like the new hotness in bipedal locomotion.

[ University of Leeds ]

I still think this is a great way of charging a robot. Make sure and watch until the end to see the detach trick.

[ YouTube ]

The Oasa R1, now on Kickstarter for $1,200, is the world’s first robotic lawn mower that uses one of them old timey reely things for cutting.

[ Kickstarter ]

ICRA next year is in Atlanta!

[ ICRA 2025 ]

Our Skunk Works team developed a modified version of the SR-71 Blackbird, titled the M-21, which carried an uncrewed reconnaissance drone called the D-21. The D-21 was designed to capture intelligence, release its camera, then self-destruct!

[ Lockheed Martin ]

The RPD 35 is a robotic powerhouse that surveys, distributes, and drives wide-flange solar piles up to 19 feet in length.

[ Built Robotics ]

Field AI’s brain technology is enabling robots to autonomously explore oil and gas facilities, navigating throughout the site and inspecting equipment for anomalies and hazardous conditions.

[ Field AI ]

Husky Observer was recently deployed at a busy automotive rail yard to carry out various autonomous inspection tasks including measuring train car positions and RFID data collection from the offloaded train inventory.

[ Clearpath ]

If you’re going to try to land a robot on the Moon, it’s useful to have a little bit of the Moon somewhere to practice on.

[ Astrobotic ]

Would you swallow a micro-robot? In a gutsy demo, physician Vivek Kumbhari navigates Pillbot, a wireless, disposable robot swallowed onstage by engineer Alex Luebke, modeling how this technology can swiftly provide direct visualization of internal organs. Learn more about how micro-robots could move us past the age of invasive endoscopies and open up doors to more comfortable, affordable medical imaging.

[ TED ]

How will AI improve our lives in the years to come? From its inception six decades ago to its recent exponential growth, futurist Ray Kurzweil highlights AI’s transformative impact on various fields and explains his prediction for the singularity: the point at which human intelligence merges with machine intelligence.

[ TED ]



Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.

RoboCup 2024: 17–22 July 2024, EINDHOVEN, NETHERLANDSICRA@40: 23–26 September 2024, ROTTERDAM, NETHERLANDSIROS 2024: 14–18 October 2024, ABU DHABI, UAEICSR 2024: 23–26 October 2024, ODENSE, DENMARKCybathlon 2024: 25–27 October 2024, ZURICH

Enjoy today’s videos!

We present Morphy, a novel compliant and morphologically aware flying robot that integrates sensorized flexible joints in its arms, thus enabling resilient collisions at high speeds and the ability to squeeze through openings narrower than its nominal dimensions.

Morphy represents a new class of soft flying robots that can facilitate unprecedented resilience through innovations both in the “body” and “brain.” The novel soft body can, in turn, enable new avenues for autonomy. Collisions that previously had to be avoided have now become acceptable risks, while areas that are untraversable for a certain robot size can now be negotiated through self-squeezing. These novel bodily interactions with the environment can give rise to new types of embodied intelligence.

[ ARL ]

Thanks, Kostas!

Segments of daily training for robots driven by reinforcement learning. Multiple tests done in advance for friendly service humans. The training includes some extreme tests. Please do not imitate!

[ Unitree ]

Sphero is not only still around, it’s making new STEM robots!

[ Sphero ]

Googly eyes mitigate all robot failures.

[ WVUIRL ]

Here I am, without the ability or equipment (or desire) required to iron anything that I own, and Flexiv’s got robots out there ironing fancy leather car seats.

[ Flexiv ]

Thanks, Noah!

We unveiled a significant leap forward in perception technology for our humanoid robot GR-1. The newly adapted pure-vision solution integrates bird’s-eye view, transformer models, and an occupancy network for precise and efficient environmental perception.

[ Fourier ]

Thanks, Serin!

LimX Dynamics’ humanoid robot CL-1 was launched in December 2023. It climbed stairs based on real-time terrain perception, two steps per stair. Four months later, in April 2024, the second demo video showcased CL-1 in the same scenario. It had advanced to climb the same stair, one step per stair.

[ LimX Dynamics ]

Thanks, Ou Yan!

New research from the University of Massachusetts Amherst shows that programming robots to create their own teams and voluntarily wait for their teammates results in faster task completion, with the potential to improve manufacturing, agriculture, and warehouse automation.

[ HCRL ] via [ UMass Amherst ]

Thanks, Julia!

LASDRA (Large-size Aerial Skeleton with Distributed Rotor Actuation system (ICRA18) is a scalable and modular aerial robot. It can assume a very slender, long, and dexterous form factor and is very lightweight.

[ SNU INRoL ]

We propose augmenting initially passive structures built from simple repeated cells, with novel active units to enable dynamic, shape-changing, and robotic applications. Inspired by metamaterials that can employ mechanisms, we build a framework that allows users to configure cells of this passive structure to allow it to perform complex tasks.

[ CMU ]

Testing autonomous exploration at the Exyn Office using Spot from Boston Dynamics. In this demo, Spot autonomously explores our flight space while on the hunt for one of our engineers.

[ Exyn ]

Meet Heavy Picker, the strongest robot in bulky-waste sorting and an absolute pro at lifting and sorting waste. With skills that would make a concert pianist jealous and a work ethic that never needs coffee breaks, Heavy Picker was on the lookout for new challenges.

[ Zen Robotics ]

AI is the biggest and most consequential business, financial, legal, technological, and cultural story of our time. In this panel, you will hear from the underrepresented community of women scientists who have been leading the AI revolution—from the beginning to now.

[ Stanford HAI ]



Insects have long been an inspiration for robots. The insect world is full of things that are tiny, fully autonomous, highly mobile, energy efficient, multimodal, self-repairing, and I could go on and on but you get the idea—insects are both an inspiration and a source of frustration to roboticists because it’s so hard to get robots to have anywhere close to insect capability.

We’re definitely making progress, though. In a paper published last month in IEEE Robotics and Automation Letters, roboticists from Shanghai Jong Tong University demonstrated the most bug-like robotic bug I think I’ve ever seen.

A Multi-Modal Tailless Flapping-Wing Robot www.youtube.com

Okay so it may not look the most bug-like, but it can do many very buggy bug things, including crawling, taking off horizontally, flying around (with six degrees of freedom control), hovering, landing, and self-righting if necessary. JT-fly weighs about 35 grams and has a wingspan of 33 centimeters, using four wings at once to fly at up to 5 meters per second and six legs to scurry at 0.3 m/s. Its 380 milliampere-hour battery powers it for an actually somewhat useful 8-ish minutes of flying and about 60 minutes of crawling.

While that amount of endurance may not sound like a lot, robots like these aren’t necessarily intended to be moving continuously. Rather, they move a little bit, find a nice safe perch, and then do some sensing or whatever until you ask them to move to a new spot. Ideally, most of that movement would be crawling, but having the option to fly makes JT-fly exponentially more useful.

Or, potentially more useful, because obviously this is still very much a research project. It does seem like there’s a bunch more optimization that could be done here; for example, JT-fly uses completely separate systems for flying and crawling, with two motors powering the legs and two additional motors powering the wings plus with two wing servos for control. There’s currently a limited amount of onboard autonomy, with an inertial measurement unit, barometer, and wireless communication, but otherwise not much in the way of useful payload.

Insects are both an inspiration and a source of frustration to roboticists because it’s so hard to get robots to have anywhere close to insect capability.

It won’t surprise you to learn that the researchers have disaster relief applications in mind for this robot, suggesting that “after natural disasters such as earthquakes and mudslides, roads and buildings will be severely damaged, and in these scenarios, JT-fly can rely on its flight ability to quickly deploy into the mission area.” One day, robots like these will actually be deployed for disaster relief, and although that day is not today, we’re just a little bit closer than we were before.

“A Multi-Modal Tailless Flapping-Wing Robot Capable of Flying, Crawling, Self-Righting and Horizontal Takeoff,” by Chaofeng Wu, Yiming Xiao, Jiaxin Zhao, Jiawang Mou, Feng Cui, and Wu Liu from Shanghai Jong Tong University, is published in the May issue of IEEE Robotics and Automation Letters.


Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.

RoboCup 2024: 17–22 July 2024, EINDHOVEN, NETHERLANDSICRA@40: 23–26 September 2024, ROTTERDAM, NETHERLANDSIROS 2024: 14–18 October 2024, ABU DHABI, UAEICSR 2024: 23–26 October 2024, ODENSE, DENMARKCybathlon 2024: 25–27 October 2024, ZURICH

Enjoy today’s videos!

There’s a Canadian legend about a flying canoe, because of course there is. The legend involves drunkenness, a party with some ladies, swearing, and a pact with the devil, because of course it does. Fortunately for the drone in this video, it needs none of that to successfully land on this (nearly) flying canoe, just some high-friction shock absorbing legs and judicious application of reverse thrust.

[ Createk ]

Thanks, Alexis!

This paper summarizes an autonomous driving project by musculoskeletal humanoids. The musculoskeletal humanoid, which mimics the human body in detail, has redundant sensors and a flexible body structure. We reconsider the developed hardware and software of the musculoskeletal humanoid Musashi in the context of autonomous driving. The respective components of autonomous driving are conducted using the benefits of the hardware and software. Finally, Musashi succeeded in the pedal and steering wheel operations with recognition.

[ Paper ] via [ JSK Lab ]

Thanks, Kento!

Robust AI has been kinda quiet for the last little while, but their Carter robot continues to improve.

[ Robust AI ]

One of the key arguments for building robots that have similar form factors to human beings is that we can leverage the massive human data for training. In this paper, we introduce a full-stack system for humanoids to learn motion and autonomous skills from human data. We demonstrate the system on our customized 33-degrees-of-freedom 180 centimeter humanoid, autonomously completing tasks such as wearing a shoe to stand up and walk, unloading objects from warehouse racks, folding a sweatshirt, rearranging objects, typing, and greeting another robot with 60-100 percent success rates using up to 40 demonstrations.

[ HumanPlus ]

We present OmniH2O (Omni Human-to-Humanoid), a learning-based system for whole-body humanoid teleoperation and autonomy. Using kinematic pose as a universal control interface, OmniH2O enables various ways for a human to control a full-sized humanoid with dexterous hands, including using real-time teleoperation through VR headset, verbal instruction, and RGB camera. OmniH2O also enables full autonomy by learning from teleoperated demonstrations or integrating with frontier models such as GPT-4.

[ OmniH2O ]

A collaboration between Boxbot, Agility Robotics, and Robust.AI at Playground Global. Make sure and watch until the end to hear the roboticists in the background react when the demo works in a very roboticist way.

::clap clap clap:: yaaaaayyyyy....

[ Robust AI ]

The use of drones and robotic devices threatens civilian and military actors in conflict areas. We started trials with robots to see how we can adapt our HEAT (Hostile Environment Awareness Training) courses to this new reality.

[ CSD ]

Thanks, Ebe!

How to make humanoids do versatile parkour jumping, clapping dance, cliff traversal, and box pick-and-move with a unified RL framework? We introduce WoCoCo: Whole-body humanoid Control with sequential Contacts

[ WoCoCo ]

A selection of excellent demos from the Learning Systems and Robotics Lab at TUM and the University of Toronto.

[ Learning Systems and Robotics Lab ]

Harvest Automation, one of the OG autonomous mobile robot companies, hasn’t updated their website since like 2016, but some videos just showed up on YouTube this week.

[ Harvest Automation ]

Northrop Grumman has been pioneering capabilities in the undersea domain for more than 50 years. Now, we are creating a new class of uncrewed underwater vehicles (UUV) with Manta Ray. Taking its name from the massive “winged” fish, Manta Ray will operate long-duration, long-range missions in ocean environments where humans can’t go.

[ Northrop Grumman ]

Akara Robotics’ autonomous robotic UV disinfection demo.

[ Akara Robotics ]

Scientists have computationally predicted hundreds of thousands of novel materials that could be promising for new technologies—but testing to see whether any of those materials can be made in reality is a slow process. Enter A-Lab, which uses robots guided by artificial intelligence to speed up the process.

[ A-Lab ]

We wrote about this research from CMU a while back, but here’s a quite nice video.

[ CMU RI ]

Aw yiss pick and place robots.

[ Fanuc ]

Axel Moore describes his lab’s work in orthopedic biomechanics to relieve joint pain with robotic assistance.

[ CMU ]

The field of humanoid robots has grown in recent years with several companies and research laboratories developing new humanoid systems. However, the number of running robots did not noticeably rise. Despite the need for fast locomotion to quickly serve given tasks, which require traversing complex terrain by running and jumping over obstacles. To provide an overview of the design of humanoid robots with bioinspired mechanisms, this paper introduces the fundamental functions of the human running gait.

[ Paper ]



The original version of this post by Benjie Holson was published on Substack here, and includes Benjie’s original comics as part of his series on robots and startups.

I worked on this idea for months before I decided it was a mistake. The second time I heard someone mention it, I thought, “That’s strange, these two groups had the same idea. Maybe I should tell them it didn’t work for us.” The third and fourth time I rolled my eyes and ignored it. The fifth time I heard about a group struggling with this mistake, I decided it was worth a blog post all on its own. I call this idea “The Mythical Non-Roboticist.”

The Mistake

The idea goes something like this: Programming robots is hard. And there are some people with really arcane skills and PhDs who are really expensive and seem to be required for some reason. Wouldn’t it be nice if we could do robotics without them? 1 What if everyone could do robotics? That would be great, right? We should make a software framework so that non-roboticists can program robots.

This idea is so close to a correct idea that it’s hard to tell why it doesn’t work out. On the surface, it’s not wrong: All else being equal, it would be good if programming robots was more accessible. The problem is that we don’t have a good recipe for making working robots. So we don’t know how to make that recipe easier to follow. In order to make things simple, people end up removing things that folks might need, because no one knows for sure what’s absolutely required. It’s like saying you want to invent an invisibility cloak and want to be able to make it from materials you can buy from Home Depot. Sure, that would be nice, but if you invented an invisibility cloak that required some mercury and neodymium to manufacture would you toss the recipe?

In robotics, this mistake is based on a very true and very real observation: Programming robots is super hard. Famously hard. It would be super great if programming robots was easier. The issue is this: Programming robots has two different kinds of hard parts.

Robots are hard because the world is complicated

Moor Studio/Getty Images

The first kind of hard part is that robots deal with the real world, imperfectly sensed and imperfectly actuated. Global mutable state is bad programming style because it’s really hard to deal with, but to robot software the entire physical world is global mutable state, and you only get to unreliably observe it and hope your actions approximate what you wanted to achieve. Getting robotics to work at all is often at the very limit of what a person can reason about, and requires the flexibility to employ whatever heuristic might work for your special problem. This is the intrinsic complexity of the problem: Robots live in complex worlds, and for every working solution there are millions of solutions that don’t work, and finding the right one is hard, and often very dependent on the task, robot, sensors, and environment.

Folks look at that challenge, see that it is super hard, and decide that, sure, maybe some fancy roboticist could solve it in one particular scenario, but what about “normal” people? “We should make this possible for non-roboticists” they say. I call these users “Mythical Non-Roboticists” because once they are programming a robot, I feel they become roboticists. Isn’t anyone programming a robot for a purpose a roboticist? Stop gatekeeping, people.

Don’t design for amorphous groups

I call also them “mythical” because usually the “non-roboticist” implied is a vague, amorphous group. Don’t design for amorphous groups. If you can’t name three real people (that you have talked to) that your API is for, then you are designing for an amorphous group and only amorphous people will like your API.

And with this hazy group of users in mind (and seeing how difficult everything is), folks think, “Surely we could make this easier for everyone else by papering over these things with simple APIs?”

No. No you can’t. Stop it.

You can’t paper over intrinsic complexity with simple APIs because if your APIs are simple they can’t cover the complexity of the problem. You will inevitably end up with a beautiful looking API, with calls like “grasp_object” and “approach_person” which demo nicely in a hackathon kickoff but last about 15 minutes of someone actually trying to get some work done. It will turn out that, for their particular application, “grasp_object()” makes 3 or 4 wrong assumptions about “grasp” and “object” and doesn’t work for them at all.

Your users are just as smart as you

This is made worse by the pervasive assumption that these people are less savvy (read: less intelligent) than the creators of this magical framework. 2 That feeling of superiority will cause the designers to cling desperately to their beautiful, simple “grasp_object()”s and resist adding the knobs and arguments needed to cover more use cases and allow the users to customize what they get.

Ironically this foists a bunch of complexity on to the poor users of the API who have to come up with clever workarounds to get it to work at all.

Moor Studio/Getty Images

The sad, salty, bitter icing on this cake-of-frustration is that, even if done really well, the goal of this kind of framework would be to expand the group of people who can do the work. And to achieve that, it would sacrifice some performance you can only get by super-specializing your solution to your problem. If we lived in a world where expert roboticists could program robots that worked really well, but there was so much demand for robots that there just wasn’t enough time for those folks to do all the programming, this would be a great solution. 3

The obvious truth is that (outside of really constrained environments like manufacturing cells) even the very best collection of real bone-fide, card-carrying roboticists working at the best of their ability struggle to get close to a level of performance that makes the robots commercially viable, even with long timelines and mountains of funding. 4 We don’t have any headroom to sacrifice power and effectiveness for ease.

What problem are we solving?

So should we give up making it easier? Is robotic development available only to a small group of elites with fancy PhDs? 5 No to both! I have worked with tons of undergrad interns who have been completely able to do robotics.6 I myself am mostly self-taught in robot programming.7 While there is a lot of intrinsic complexity in making robots work, I don’t think there is any more than, say, video game development.

In robotics, like in all things, experience helps, some things are teachable, and as you master many areas you can see things start to connect together. These skills are not magical or unique to robotics. We are not as special as we like to think we are.

But what about making programming robots easier? Remember way back at the beginning of the post when I said that there were two different kinds of hard parts? One is the intrinsic complexity of the problem, and that one will be hard no matter what. 8 But the second is the incidental complexity, or as I like to call it, the stupid BS complexity.

Stupid BS Complexity

Robots are asynchronous, distributed, real-time systems with weird hardware. All of that will be hard to configure for stupid BS reasons. Those drivers need to work in the weird flavor of Linux you want for hard real-time for your controls and getting that all set up will be hard for stupid BS reasons. You are abusing Wi-Fi so you can roam seamlessly without interruption but Linux’s Wi-Fi will not want to do that. Your log files are huge and you have to upload them somewhere so they don’t fill up your robot. You’ll need to integrate with some cloud something or other and deal with its stupid BS. 9

Moor Studio/Getty Images

There is a ton of crap to deal with before you even get to complexity of dealing with 3D rotation, moving reference frames, time synchronization, messaging protocols. Those things have intrinsic complexity (you have to think about when something was observed and how to reason about it as other things have moved) and stupid BS complexity (There’s a weird bug because someone multiplied two transform matrices in the wrong order and now you’re getting an error message that deep in some protocol a quaternion is not normalized. WTF does that mean?) 10

One of the biggest challenges of robot programming is wading through the sea of stupid BS you need to wrangle in order to start working on your interesting and challenging robotics problem.

So a simple heuristic to make good APIs is:

Design your APIs for someone as smart as you, but less tolerant of stupid BS.

That feels universal enough that I’m tempted to call it Holson’s Law of Tolerable API Design.

When you are using tools you’ve made, you know them well enough to know the rough edges and how to avoid them.

But rough edges are things that have to be held in a programmer’s memory while they are using your system. If you insist on making a robotics framework 11, you should strive to make it as powerful as you can with the least amount of stupid BS. Eradicate incidental complexity everywhere you can. You want to make APIs that have maximum flexibility but good defaults. I like python’s default-argument syntax for this because it means you can write APIs that can be used like:

It is possible to have easy things be simple and allow complex things. And please, please, please don’t make condescending APIs. Thanks!

1. Ironically it is very often the expensive arcane-knowledge-having PhDs who are proposing this.

2. Why is it always a framework?

3. The exception that might prove the rule is things like traditional manufacturing-cell automation. That is a place where the solutions exist, but the limit to expanding is set up cost. I’m not an expert in this domain, but I’d worry that physical installation and safety compliance might still dwarf the software programming cost, though.

4. As I well know from personal experience.

5. Or non-fancy PhDs for that matter?

6. I suspect that many bright highschoolers would also be able to do the work. Though, as Google tends not to hire them, I don’t have good examples.

7. My schooling was in Mechanical Engineering and I never got a PhD, though my ME classwork did include some programming fundamentals.

8. Unless we create effective general purpose AI. It feels weird that I have to add that caveat, but the possibility that it’s actually coming for robotics in my lifetime feels much more possible than it did two years ago.

9. And if you are unlucky, its API was designed by someone who thought they were smarter than their customers.

10. This particular flavor of BS complexity is why I wrote posetree.py. If you do robotics, you should check it out.

11. Which, judging by the trail of dead robot-framework-companies, is a fraught thing to do.



Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.

RoboCup 2024: 17–22 July 2024, EINDHOVEN, NETHERLANDSICRA@40: 23–26 September 2024, ROTTERDAM, NETHERLANDSIROS 2024: 14–18 October 2024, ABU DHABI, UNITED ARAB EMIRATESICSR 2024: 23–26 October 2024, ODENSE, DENMARKCybathlon 2024: 25–27 October 2024, ZURICH

Enjoy today’s videos!

In this video, you see the start of 1X’s development of an advanced AI system that chains simple tasks into complex actions using voice commands, allowing seamless multi-robot control and remote operation. By starting with single-task models, we ensure smooth transitions to more powerful unified models, ultimately aiming to automate high-level actions using AI.

This video does not contain teleoperation, computer graphics, cuts, video speedups, or scripted trajectory playback. It’s all controlled via neural networks.

[ 1X ]

As the old adage goes, one cannot claim to be a true man without a visit to the Great Wall of China. XBot-L, a full-sized humanoid robot developed by Robot Era, recently acquitted itself well in a walk along sections of the Great Wall.

[ Robot Era ]

The paper presents a novel rotary wing platform, that is capable of folding and expanding its wings during flight. Our source of inspiration came from birds’ ability to fold their wings to navigate through small spaces and dive. The design of the rotorcraft is based on the monocopter platform, which is inspired by the flight of Samara seeds.

[ AirLab ]

We present a variable stiffness robotic skin (VSRS), a concept that integrates stiffness-changing capabilities, sensing, and actuation into a single, thin modular robot design. Reconfiguring, reconnecting, and reshaping VSRSs allows them to achieve new functions both on and in the absence of a host body.

[ Yale Faboratory ]

Heimdall is a new rover design for the 2024 University Rover Challenge (URC). This video shows highlights of Heimdall’s trip during the four missions at URC 2024.

Heimdall features a split body design with whegs (wheel legs), and a drill for sub-surface sample collection. It also has the ability to manipulate a variety of objects, collect surface samples, and perform onboard spectrometry and chemical tests.

[ WVU ]

I think this may be the first time I’ve seen an autonomous robot using a train? This one is delivering lunch boxes!

[ JSME ]

The AI system used identifies and separates red apples from green apples, after which a robotic arm picks up the red apples identified with a qb SoftHand Industry and gently places them in a basket.

My favorite part is the magnetic apple stem system.

[ QB Robotics ]

DexNex (v0, June 2024) is an anthropomorphic teleoperation testbed for dexterous manipulation at the Center for Robotics and Biosystems at Northwestern University. DexNex recreates human upper-limb functionality through a near 1-to-1 mapping between Operator movements and Avatar actions.

Motion of the Operator’s arms, hands, fingers, and head are fed forward to the Avatar, while fingertip pressures, finger forces, and camera images are fed back to the Operator. DexNex aims to minimize the latency of each subsystem to provide a seamless, immersive, and responsive user experience. Future research includes gaining a better understanding of the criticality of haptic and vision feedback for different manipulation tasks; providing arm-level grounded force feedback; and using machine learning to transfer dexterous skills from the human to the robot.

[ Northwestern ]

Sometimes the best path isn’t the smoothest or straightest surface, it’s the path that’s actually meant to be a path.

[ RaiLab ]

Fulfilling a school requirement by working in a Romanian locomotive factory one week each month, Daniela Rus learned to operate “machines that help us make things.” Appreciation for the practical side of math and science stuck with Daniela, who is now Director of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).

[ MIT ]

For AI to achieve its full potential, non-experts need to be let into the development process, says Rumman Chowdhury, CEO and cofounder of Humane Intelligence. She tells the story of farmers fighting for the right to repair their own AI-powered tractors (which some manufacturers actually made illegal), proposing everyone should have the ability to report issues, patch updates or even retrain AI technologies for their specific uses.

[ TED ]



Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.

RoboCup 2024: 17–22 July 2024, EINDHOVEN, NETHERLANDSICSR 2024: 23–26 October 2024, ODENSE, DENMARKCybathlon 2024: 25–27 October 2024, ZURICH

Enjoy today’s videos!

Do you have trouble multitasking? Cyborgize yourself through muscle stimulation to automate repetitive physical tasks while you focus on something else.

[ SplitBody ]

By combining a 5,000 frame-per-second (FPS) event camera with a 20-FPS RGB camera, roboticists from the University of Zurich have developed a much more effective vision system that keeps autonomous cars from crashing into stuff, as described in the current issue of Nature.

[ Nature ]

Mitsubishi Electric has been awarded the GUINNESS WORLD RECORDS title for the fastest robot to solve a puzzle cube. The robot’s time of 0.305 second beat the previous record of 0.38 second, for which it received a GUINNESS WORLD RECORDS certificate on 21 May 2024.

[ Mitsubishi ]

Sony’s AIBO is celebrating its 25th anniversary, which seems like a long time, and it is. But back then, the original AIBO could check your email for you. Email! In 1999!

I miss Hotmail.

[ AIBO ]

SchniPoSa: schnitzel with french fries and a salad.

[ Dino Robotics ]

Cloth-folding is still a really hard problem for robots, but progress was made at ICRA!

[ ICRA Cloth Competition ]

Thanks, Francis!

MIT CSAIL researchers enhance robotic precision with sophisticated tactile sensors in the palm and agile fingers, setting the stage for improvements in human-robot interaction and prosthetic technology.

[ MIT ]

We present a novel adversarial attack method designed to identify failure cases in any type of locomotion controller, including state-of-the-art reinforcement-learning-based controllers. Our approach reveals the vulnerabilities of black-box neural network controllers, providing valuable insights that can be leveraged to enhance robustness through retraining.

[ Fan Shi ]

In this work, we investigate a novel integrated flexible OLED display technology used as a robotic skin-interface to improve robot-to-human communication in a real industrial setting at Volkswagen or a collaborative human-robot interaction task in motor assembly. The interface was implemented in a workcell and validated qualitatively with a small group of operators (n=9) and quantitatively with a large group (n=42). The validation results showed that using flexible OLED technology could improve the operators’ attitude toward the robot; increase their intention to use the robot; enhance their perceived enjoyment, social influence, and trust; and reduce their anxiety.

[ Paper ]

Thanks, Bram!

We introduce InflatableBots, shape-changing inflatable robots for large-scale encountered-type haptics in VR. Unlike traditional inflatable shape displays, which are immobile and limited in interaction areas, our approach combines mobile robots with fan-based inflatable structures. This enables safe, scalable, and deployable haptic interactions on a large scale.

[ InflatableBots ]

We present a bioinspired passive dynamic foot in which the claws are actuated solely by the impact energy. Our gripper simultaneously resolves the issue of smooth absorption of the impact energy and fast closure of the claws by linking the motion of an ankle linkage and the claws through soft tendons.

[ Paper ]

In this video, a 3-UPU exoskeleton robot for a wrist joint is designed and controlled to perform wrist extension, flexion, radial-deviation, and ulnar-deviation motions in stroke-affected patients. This is the first time a 3-UPU robot has been used effectively for any kind of task.

“UPU” stands for “universal-prismatic-universal” and refers to the actuators—the prismatic joints between two universal joints.

[ BAS ]

Thanks, Tony!

BRUCE Got Spot-ted at ICRA2024.

[ Westwood Robotics ]

Parachutes: maybe not as good of an idea for drones as you might think.

[ Wing ]

In this paper, we propose a system for the artist-directed authoring of stylized bipedal walking gaits, tailored for execution on robotic characters. To demonstrate the utility of our approach, we animate gaits for a custom, free-walking robotic character, and show, with two additional in-simulation examples, how our procedural animation technique generalizes to bipeds with different degrees of freedom, proportions, and mass distributions.

[ Disney Research ]

The European drone project Labyrinth aims to keep new and conventional air traffic separate, especially in busy airspaces such as those expected in urban areas. The project provides a new drone-traffic service and illustrates its potential to improve the safety and efficiency of civil land, air, and sea transport, as well as emergency and rescue operations.

[ DLR ]

This Carnegie Mellon University Robotics Institute seminar, by Kim Baraka at Vrije Universiteit Amsterdam, is on the topic “Why We Should Build Robot Apprentices and Why We Shouldn’t Do It Alone.”

For robots to be able to truly integrate human-populated, dynamic, and unpredictable environments, they will have to have strong adaptive capabilities. In this talk, I argue that these adaptive capabilities should leverage interaction with end users, who know how (they want) a robot to act in that environment. I will present an overview of my past and ongoing work on the topic of human-interactive robot learning, a growing interdisciplinary subfield that embraces rich, bidirectional interaction to shape robot learning. I will discuss contributions on the algorithmic, interface, and interaction design fronts, showcasing several collaborations with animal behaviorists/trainers, dancers, puppeteers, and medical practitioners.

[ CMU RI ]

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