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.

Enjoy today’s videos!

This video about ‘foster’ Aibos helping kids at a children’s hospital is well worth turning on auto-translated subtitles for.

[ Aibo Foster Program ]

[ Unitree ]

Happy Chinese New Year from PNDbotics!

[ PNDbotics ]

[ LimX Dynamics ]

Mr. Bucket is my favorite.

[ Mitsubishi Electric Research Laboratories ]

Thanks, Yuki!

[ Zoox ]

The Humanoids Summit at the Computer History Museum in December was successful enough (either because of or in spite of my active participation) that it’s not only happening again in 2025: There’s also going to be a spring version of the conference in London in May!

[ Humanoids Summit ]

I’m not sure it’ll ever be practical at scale, but I do really like JSK’s musculoskeletal humanoid work.

[ Paper ]

[ Canadian Space Agency ]

[ Corvus Robotics ]

Thanks, Joan!

I would have said that this controller was too small to be manipulated with a pinch grasp. I would be wrong.

[ Pollen ]

[ NASA ]

[ Team BlackSheep ]

[ Zoox ]

Most people know that robots no longer sound like tinny trash cans. They sound like Siri, Alexa, and Gemini. They sound like the voices in labyrinthine customer support phone trees. And even those robot voices are being made obsolete by new AI-generated voices that can mimic every vocal nuance and tic of human speech, down to specific regional accents. And with just a few seconds of audio, AI can now clone someone’s specific voice.

This technology will replace humans in many areas. Automated customer support will save money by cutting staffing at call centers. AI agents will make calls on our behalf, conversing with others in natural language. All of that is happening, and will be commonplace soon.

But there is something fundamentally different about talking with a bot as opposed to a person. A person can be a friend. An AI cannot be a friend, despite how people might treat it or react to it. AI is at best a tool, and at worst a means of manipulation. Humans need to know whether we’re talking with a living, breathing person or a robot with an agenda set by the person who controls it. That’s why robots should sound like robots.

You can’t just label AI-generated speech. It will come in many different forms. So we need a way to recognize AI that works no matter the modality. It needs to work for long or short snippets of audio, even just a second long. It needs to work for any language, and in any cultural context. At the same time, we shouldn’t constrain the underlying system’s sophistication or language complexity.

We have a simple proposal: all talking AIs and robots should use a ring modulator. In the mid-twentieth century, before it was easy to create actual robotic-sounding speech synthetically, ring modulators were used to make actors’ voices sound robotic. Over the last few decades, we have become accustomed to robotic voices, simply because text-to-speech systems were good enough to produce intelligible speech that was not human-like in its sound. Now we can use that same technology to make robotic speech that is indistinguishable from human sound robotic again.

A ring modulator has several advantages: It is computationally simple, can be applied in real-time, does not affect the intelligibility of the voice, and--most importantly--is universally “robotic sounding” because of its historical usage for depicting robots.

Responsible AI companies that provide voice synthesis or AI voice assistants in any form should add a ring modulator of some standard frequency (say, between 30-80 Hz) and of a minimum amplitude (say, 20 percent). That’s it. People will catch on quickly.

Here are a couple of examples you can listen to for examples of what we’re suggesting. The first clip is an AI-generated “podcast” of this article made by Google’s NotebookLM featuring two AI “hosts.” Google’s NotebookLM created the podcast script and audio given only the text of this article. The next two clips feature that same podcast with the AIs’ voices modulated more and less subtly by a ring modulator:

Raw audio sample generated by Google’s NotebookLM Your browser does not support the audio element.

Audio sample with added ring modulator (30 Hz-25%) Your browser does not support the audio element.

Audio sample with added ring modulator (30 Hz-40%) Your browser does not support the audio element.

We were able to generate the audio effect with a 50-line Python script generated by Anthropic’s Claude. One of the most well-known robot voices were those of the Daleks from Doctor Who in the 1960s. Back then robot voices were difficult to synthesize, so the audio was actually an actor’s voice run through a ring modulator. It was set to around 30 Hz, as we did in our example, with different modulation depth (amplitude) depending on how strong the robotic effect is meant to be. Our expectation is that the AI industry will test and converge on a good balance of such parameters and settings, and will use better tools than a 50-line Python script, but this highlights how simple it is to achieve.

Of course there will also be nefarious uses of AI voices. Scams that use voice cloning have been getting easier every year, but they’ve been possible for many years with the right know-how. Just like we’re learning that we can no longer trust images and videos we see because they could easily have been AI-generated, we will all soon learn that someone who sounds like a family member urgently requesting money may just be a scammer using a voice-cloning tool.

We don’t expect scammers to follow our proposal: They’ll find a way no matter what. But that’s always true of security standards, and a rising tide lifts all boats. We think the bulk of the uses will be with popular voice APIs from major companies--and everyone should know that they’re talking with a robot.

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

Swarms of autonomous robots are increasingly being tested and deployed in complex missions, yet a certain level of human oversight during these missions is still required. Which means a major question remains: How many robots—and how complex a mission—can a single human manage before becoming overwhelmed?

In a study funded by the U.S. Defense Advanced Research Projects Agency (DARPA), experts show that humans can single-handedly and effectively manage a heterogenous swarm of more than 100 autonomous ground and aerial vehicles, while feeling overwhelmed only for brief periods of time during an overall small portion of the mission. For instance, in a particularly challenging, multi-day experiment in an urban setting, human controllers were overloaded with stress and workload only three percent of the time. The results were published 19 November in IEEE Transactions on Field Robotics.

Julie A. Adams, the associate director of research at Oregon State University’s Collaborative Robotics and Intelligent Systems Institute, has been studying human interactions with robots and other complex systems, such as aircraft cockpits and nuclear power plant control rooms, for 35 years. She notes that robot swarms can be used to support missions where work may be particularly dangerous and hazardous for humans, such as monitoring wildfires.

“Swarms can be used to provide persistent coverage of an area, such as monitoring for new fires or looters in the recently burned areas of Los Angeles,” Adams says. “The information can be used to direct limited assets, such as firefighting units or water tankers to new fires and hotspots, or to locations at which fires were thought to have been extinguished.”

These kinds of missions can involve a mix of many different kinds of unmanned ground vehicles (such as the Aion Robotics R1 wheeled robot) and aerial autonomous vehicles (like the Modal AI VOXL M500 quadcopter), and a human controller may need to reassign individual robots to different tasks as the mission unfolds. Notably, some theories over the past few decades—and even Adams’ early thesis work—suggest that a single human has limited capacity to deploy very large numbers of robots.

“These historical theories and the associated empirical results showed that as the number of ground robots increased, so did the human’s workload, which often resulted in reduced overall performance,” says Adams, noting that, although earlier research focused on unmanned ground vehicles (UGVs), which must deal with curbs and other physical barriers, unmanned aerial vehicles (UAVs) often encounter fewer physical barriers.

Human controllers managed their swarms of autonomous vehicles with a virtual display. The fuschia ring represents the area the person could see within their head-mounted display.DARPA

As part of DARPA’s OFFensive Swarm-Enabled Tactics (OFFSET) program, Adams and her colleagues sought to explore whether these theories applied to very complex missions involving a mix of unmanned ground and air vehicles. In November 2021, at Fort Campbell in Kentucky, two human controllers took turns engaging in a series of missions over the course of three weeks with the objective of neutralizing an adversarial target. Both human controllers had significant experience controlling swarms, and participated in alternating shifts that ranged from 1.5 to 3 hours per day.

During the tests, the human controllers were positioned in a designated area on the edge of the testing site, and used a virtual reconstruction of the environment to keep tabs on where vehicles were and what tasks they were assigned to.

The largest mission shift involved 110 drones, 30 ground vehicles, and up to 50 virtual vehicles representing additional real-world vehicles. The robots had to navigate through the physical urban environment, as well as a series of virtual hazards represented using AprilTags—simplified QR codes that could represent imaginary hazards—that were scattered throughout the mission site.

DARPA made the final field exercise exceptionally challenging by providing thousands of hazards and pieces of information to inform the search. “The complexity of the hazards was significant,” Adams says, noting that some hazards required multiple robots to interact with them simultaneously, and some hazards moved around the environment.

Throughout each mission shift, the human controller’s physiological responses to the tasks at hand were monitored. For example, sensors collected data on their heart-rate variability, posture, and even their speech rate. The data were input into an established algorithm that estimates workload levels and was used to determine when the controller was reaching a workload level that exceeded a normal range, called an “overload state.”

Adams notes that, despite the complexity and large volume of robots to manage in this field exercise, the number and duration of overload state instances were relatively short—a handful of minutes during a mission shift. “The total percentage of estimated overload states was 3 percent of all workload estimates across all shifts for which we collected data,” she says.

www.youtube.com

The most common reason for a human commander to reach an overload state is when they had to generate multiple new tactics or inspect which vehicles in the launch zone were available for deployment.

Adams notes that these finding suggest that—counter to past theories—the number of robots may be less influential on human swarm control performance than previously thought. Her team is exploring the other factors that may impact swarm control missions, such as other human limitations, system designs and UAS designs, the results of which will potentially inform US Federal Aviation Administration drone regulations, she says.

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.

Enjoy today’s videos!

Are wheeled quadrupeds going to run out of crazy new ways to move anytime soon? Looks like maybe not.

[ Deep Robotics ]

A giant eye and tiny feet make this pipe inspection robot exceptionally cute, I think.

[ tmsuk ] via [ Robotstart ]

Agility seems to be one of the few humanoid companies talking seriously about safety.

[ Agility Robotics ]

[ University of Michigan ]

[ Paper ]

Thanks, Kento!

If I’m understanding this correctly, if you’re careful, it’s possible to introduce chaos into a blind juggling robot to switch synced juggling to alternate juggling.

[ ETH Zurich ]

Drones with beaks? Sure, why not.

[ GRVC ]

[ OLogic ]

[ University of Texas at Austin ]

Seabed observation plays a major role in safeguarding marine systems by keeping tabs on the species and habitats on the ocean floor at different depths. This is primarily done by underwater robots that use optical imaging to collect high quality data that can be fed into environmental models, and compliment the data obtained through sonar in large-scale ocean observations.

Different underwater robots have been trialed over the years, but many have struggled with performing near-seabed observations because they disturb the local seabed by destroying coral and disrupting the sediment. Gang Wang, from Harbin Engineering University in China, and his research team have recently developed a maneuverable underwater vehicle that is better suited to seabed operations because it doesn’t disturb the local environment by floating above the seabed and possessing a specially engineering propeller system to manuever. These robots could be used to better protect the seabed while studying it, and improve efforts to preserve marine biodiversity and explore for underwater resources such as minerals for EV batteries.

Many underwater robots are wheeled or legged, but “these robots face substantial challenges in rugged terrains where obstacles and slopes can impede their functionality,” says Wang. They can also damage coral reefs.

Floating robots don’t have this issue, but existing options disturb the sediment on the seabed because their thrusters create a downward current during ascension. The waves generated as the propeller’s wake directly hit the seafloor in most floating robots, which causes sediment to move in the immediate vicinity. In a similar way to dust blowing in front of your digital or smartphone camera, the particles moving through the water can obscure the view of the cameras on the robot and reduce the quality of the images it captures. “Addressing this issue was crucial for the functional success of our prototype and for increasing its acceptance among engineers,” says Wang.

After further investigation, Wang and the rest of the team found that the robot’s shape influences the local water resistance, or drag, even at low speeds. “During the design process, we configured the robot with two planes exhibiting significant differences in water resistance,” says Wang. This led to the researchers developing a robot with a flattened body and angling the thruster relative to the central axis. “We found that the robot’s shape and the thruster layout significantly influence its ascent speed,” says Wang.

Clockwise from left: relationship between rotational speed of the thruster and the resultant force and torque in the airframe coordinate system, overall structure of the robot, side view of the thruster arrangement and main electronics components.Gang Wang, Kaixin Liu et al.

The researchers created a navigational system where the thrusters generate a combined force that slants downwards but still allows the robot to ascend, changing the wake distribution during ascent so that it doesn’t disturb the sediment on the seafloor. “Flattening the robot’s body and angling the thruster relative to the central axis is a straightforward approach for most engineers, enhancing the potential for broader application of this design” in seabed monitoring, says Wang.

“By addressing the navigational concerns of floating robots, we aim to enhance the observational capabilities of underwater robots in near-seafloor environments,” says Wang. The vehicle was tested in a range of marine environments, including sandy areas, coral reefs, and sheer rock, to show its ability to minimally disturb sediments in multiple potential environments.

Alongside the structural design advancements, the team incorporated an angular acceleration feedback control to keep the robot as close to the seafloor as possible without actually hitting it—called bottoming out. They also developed external disturbance observation algorithms and designed a sensor layout structure that enables the robot to quickly recognize and resist external disturbances, as well as plot a path in real time. This approach allowed the new vehicle to travel along at only 20 centimeters above the seafloor without bottoming out.

By implanting this control, the robot was able to get close to the sea floor and improve the quality of the images it took by reducing light refraction and scattering caused by the water column. “Given the robot’s proximity to the seafloor, even brief periods of instability can lead to collisions with the bottom, and we have verified that the robot shows excellent resistance to strong disturbances,” says Wang.

With the success of this new robot achieving a closer approach to the seafloor without disturbing the seabed or crashing, Wang has stated that they plan to use the robot to closely observe coral reefs. Coral reef monitoring currently relies on inefficient manual methods, so the robots could widen the areas that are observed, and do so more quickly.

Wang adds that “effective detection methods are lacking in deeper waters, particularly in the mid-light layer. We plan to improve the autonomy of the detection process to substitute divers in image collection, and facilitate the automatic identification and classification of coral reef species density to provide a more accurate and timely feedback on the health status of coral reefs.”

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.

Enjoy today's videos!

[ Unitree ]

This is just lovely.

[ Mimus CNK ]

There’s a lot to like about Grain Weevil as an effective unitasking robot, but what I really appreciate here is that the control system is just a remote and a camera slapped onto the top of the bin.

[ Grain Weevil ]

This video, “Robot arm picking your groceries like a real person,” has taught me that I am not a real person.

[ Extend Robotics ]

A robot walking like a human walking like what humans think a robot walking like a robot walks like.

And that was my favorite sentence of the week.

[ Engineai ]

[ Pollen Robotics ]

So a thing that I have come to understand about ships with sails (thanks, Jack Aubrey!) is that sailing in the direction that the wind is coming from can be tricky. Turns out that having a boat with two fronts and no back makes this a lot easier.

[ Paper ] from [ 2023 IEEE/ASME International Conference on Advanced Intelligent Mechatronics ] via [ IEEE Xplore ]

[ Paper ]

Thanks, Kento!

[ Cybathlon ]

Thanks, Robert!

If you’re going to work on robot dogs, I’m honestly not sure whether Purina would be the most or least appropriate place to do that.

[ Michigan Robotics ]

In 1942, the legendary science fiction author Isaac Asimov introduced his Three Laws of Robotics in his short story “Runaround.” The laws were later popularized in his seminal story collection I, Robot.

• First Law: A robot may not injure a human being or, through inaction, allow a human being to come to harm.
• Second Law: A robot must obey orders given it by human beings except where such orders would conflict with the First Law.
• Third Law: A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

While drawn from works of fiction, these laws have shaped discussions of robot ethics for decades. And as AI systems—which can be considered virtual robots—have become more sophisticated and pervasive, some technologists have found Asimov’s framework useful for considering the potential safeguards needed for AI that interacts with humans.

But the existing three laws are not enough. Today, we are entering an era of unprecedented human-AI collaboration that Asimov could hardly have envisioned. The rapid advancement of generative AI capabilities, particularly in language and image generation, has created challenges beyond Asimov’s original concerns about physical harm and obedience.

The proliferation of AI-enabled deception is particularly concerning. According to the FBI’s 2024 Internet Crime Report, cybercrime involving digital manipulation and social engineering resulted in losses exceeding US $10.3 billion. The European Union Agency for Cybersecurity’s 2023 Threat Landscape specifically highlighted deepfakes—synthetic media that appears genuine—as an emerging threat to digital identity and trust.

Social media misinformation is spreading like wildfire. I studied it during the pandemic extensively and can only say that the proliferation of generative AI tools has made its detection increasingly difficult. To make matters worse, AI-generated articles are just as persuasive or even more persuasive than traditional propaganda, and using AI to create convincing content requires very little effort.

Deepfakes are on the rise throughout society. Botnets can use AI-generated text, speech, and video to create false perceptions of widespread support for any political issue. Bots are now capable of making and receiving phone calls while impersonating people. AI scam calls imitating familiar voices are increasingly common, and any day now, we can expect a boom in video call scams based on AI-rendered overlay avatars, allowing scammers to impersonate loved ones and target the most vulnerable populations. Anecdotally, my very own father was surprised when he saw a video of me speaking fluent Spanish, as he knew that I’m a proud beginner in this language (400 days strong on Duolingo!). Suffice it to say that the video was AI-edited.

Even more alarmingly, children and teenagers are forming emotional attachments to AI agents, and are sometimes unable to distinguish between interactions with real friends and bots online. Already, there have been suicides attributed to interactions with AI chatbots.

In his 2019 book Human Compatible, the eminent computer scientist Stuart Russell argues that AI systems’ ability to deceive humans represents a fundamental challenge to social trust. This concern is reflected in recent policy initiatives, most notably the European Union’s AI Act, which includes provisions requiring transparency in AI interactions and transparent disclosure of AI-generated content. In Asimov’s time, people couldn’t have imagined how artificial agents could use online communication tools and avatars to deceive humans.

Therefore, we must make an addition to Asimov’s laws.

• Fourth Law: A robot or AI must not deceive a human by impersonating a human being.

We need clear boundaries. While human-AI collaboration can be constructive, AI deception undermines trust and leads to wasted time, emotional distress, and misuse of resources. Artificial agents must identify themselves to ensure our interactions with them are transparent and productive. AI-generated content should be clearly marked unless it has been significantly edited and adapted by a human.

Implementation of this Fourth Law would require:

• Mandatory AI disclosure in direct interactions,
• Clear labeling of AI-generated content,
• Technical standards for AI identification,
• Legal frameworks for enforcement,
• Educational initiatives to improve AI literacy.

Of course, all this is easier said than done. Enormous research efforts are already underway to find reliable ways to watermark or detect AI-generated text, audio, images, and videos. Creating the transparency I’m calling for is far from a solved problem.

But the future of human-AI collaboration depends on maintaining clear distinctions between human and artificial agents. As noted in the IEEE’s 2022 “Ethically Aligned Design“ framework, transparency in AI systems is fundamental to building public trust and ensuring the responsible development of artificial intelligence.

Asimov’s complex stories showed that even robots that tried to follow the rules often discovered the unintended consequences of their actions. Still, having AI systems that are trying to follow Asimov’s ethical guidelines would be a very good start.

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.

Enjoy today’s videos!

I’m not totally sure yet about the utility of having a small arm on a robot vacuum, but I love that this is a real thing. At least, it is at CES this year.

[ Roborock ]

We posted about SwitchBot’s new modular home robot system earlier this week, but here’s a new video showing some potentially useful hardware combinations.

[ SwitchBot ]

Yes, it’s in sim, but (and this is a relatively new thing) I will not be shocked to see this happen on Unitree’s hardware in the near future.

[ Unitree ]

[ LimX Dynamics ]

We’ve seen hybrid quadrotor bipeds before, but this one , which is imitating the hopping behavior of Jacana birds, is pretty cute.

What’s a Jacana bird, you ask? It’s these things, which surely must have the most extreme foot to body ratio of any bird:

Also, much respect to the researchers for confidently titling this supplementary video “An Extremely Elegant Jump.”

[ SSRN Paper preprint ]

Twelve minutes flat from suitcase to mobile manipulator. Not bad!

[ Pollen Robotics ]

Happy New Year from Dusty Robotics!

[ Dusty Robotics ]

Back in the day, the defining characteristic of home-cleaning robots was that they’d randomly bounce around your floor as part of their cleaning process, because the technology required to localize and map an area hadn’t yet trickled down into the consumer space. That all changed in 2010, when home robots started using lidar (and other things) to track their location and optimize how they cleaned.

Consumer pool-cleaning robots are lagging about 15 years behind indoor robots on this, for a couple of reasons. First, most pool robots—different from automatic pool cleaners, which are purely mechanical systems that are driven by water pressure—have been tethered to an outlet for power, meaning that maximizing efficiency is less of a concern. And second, 3D underwater localization is a much different (and arguably more difficult) problem to solve than 2D indoor localization was. But pool robots are catching up, and at CES this week, Wybot introduced an untethered robot that uses ultrasound to generate a 3D map for fast, efficient pool cleaning. And it’s solar powered and self-emptying, too.

Underwater localization and navigation is not an easy problem for any robot. Private pools are certainly privileged to be operating environments with a reasonable amount of structure and predictability, at least if everything is working the way it should. But the lighting is always going to be a challenge, between bright sunlight, deep shadow, wave reflections, and occasionally murky water if the pool chemicals aren’t balanced very well. That makes relying on any light-based localization system iffy at best, and so Wybot has gone old school, with ultrasound.

Ultrasound used to be a very common way for mobile robots to navigate. You may (or may not) remember venerable robots like the Pioneer 3, with those big ultrasonic sensors across its front. As cameras and lidar got cheap and reliable, the messiness of ultrasonic sensors fell out of favor, but sound is still ideal for underwater applications where anything that relies on light may struggle.

The Wybot S3 uses 12 ultrasonic sensors, plus motor encoders and an inertial measurement unit to map residential pools in three dimensions. “We had to choose the ultrasonic sensors very carefully,” explains Felix (Huo) Feng, the CTO of Wybot. “Actually, we use multiple different sensors, and we compute time of flight [of the sonar pulses] to calculate distance.” The positional accuracy of the resulting map is about 10 centimeters, which is totally fine for the robot to get its job done, although Feng says that they’re actively working to improve the map’s resolution. For path planning purposes, the 3D map gets deconstructed into a series of 2D maps, since the robot needs to clean the bottom of the pool, stairs and ledges, and also the sides of the pool.

Efficiency is particularly important for the S3 because its charging dock has enough solar panels on the top of it to provide about 90 minutes of runtime for the robot over the course of an optimally sunny day. If your pool isn’t too big, that means the robot can clean it daily without requiring a power connection to the dock. The dock also sucks debris out of the collection bin on the robot itself, and Wybot suggests that the S3 can go for up to a month of cleaning without the dock overflowing.

The S3 has a camera on the front, which is used primarily to identify and prioritize dirtier areas (through AI, of course) that need focused cleaning. At some point in the future, Wybot may be able to use vision for navigation too, but my guess is that for reliable 24/7 navigation, ultrasound will still be necessary.

One other interesting little tidbit is the communication system. The dock can talk to your Wi-Fi, of course, and then talk to the robot while it’s charging. Once the robot goes off for a swim, however, traditional wireless signals won’t work, but the dock has its own sonar that can talk to the robot at several bytes per second. This isn’t going to get you streaming video from the robot’s camera, but it’s enough to let you steer the robot if you want, or ask it to come back to the dock, get battery status updates, and similar sorts of things.

The Wybot S3 will go on sale in Q2 of this year for a staggering US $2,999, but that’s how it always works: The first time a new technology shows up in the consumer space, it’s inevitably at a premium. Give it time, though, and my guess is that the ability to navigate and self-empty will become standard features in pool robots. But as far as I know, Wybot got there first.

Autonomous systems, particularly fleets of drones and other unmanned vehicles, face increasing risks as their complexity grows. Despite advancements, existing testing frameworks fall short in addressing end-to-end security, resilience, and safety in zero-trust environments. The Secure Systems Research Center (SSRC) at TII has developed a rigorous, holistic testing framework to systematically evaluate the performance and security of these systems at each stage of development. This approach ensures secure, resilient, and safe operations for autonomous systems, from individual components to fleet-wide interactions.

Earlier this year, we reviewed the SwitchBot S10, a vacuuming and wet mopping robot that uses a water-integrated docking system to autonomously manage both clean and dirty water for you. It’s a pretty clever solution, and we appreciated that SwitchBot was willing to try something a little different.

At CES this week, SwitchBot introduced the K20+ Pro, a little autonomous vacuum that can integrate with a bunch of different accessories by pulling them around on a backpack cart of sorts. The K20+ Pro is SwitchBot’s latest effort to explore what’s possible with mobile home robots.

SwitchBot’s small vacuum can transport different payloads on top.SwitchBot

What we’re looking at here is a “mini” robotic vacuum (it’s about 25 centimeters in diameter) that does everything a robotic vacuum does nowadays: It uses lidar to make a map of your house so that you can direct it where to go, it’s got a dock to empty itself and recharge, and so on. The mini robotic vacuum is attached to a wheeled platform that SwitchBot is calling a “FusionPlatform” that sits on top of the robot like a hat. The vacuum docks to this platform, and then the platform will go wherever the robot goes. This entire system (robot, dock, and platform) is the “K20+ Pro multitasking household robot.”

SwitchBot refers to the K20+ Pro as a “smart delivery assistant,” because you can put stuff on the FusionPlatform and the K20+ Pro will move that stuff around your house for you. This really doesn’t do it justice, though, because the platform is much more than just a passive mobile cart. It also can provide power to a bunch of different accessories, all of which benefit from autonomous mobility:

The SwitchBot can carry a variety of payloads, including custom payloads.SwitchBot

From left to right, you’re looking at an air circulation fan, a tablet stand, a vacuum and charging dock and an air purifier and security camera (and a stick vacuum for some reason), and lastly just the air purifier and security setup. You can also add and remove different bits, like if you want the fan along with the security camera, just plop the security camera down on the platform base in front of the fan and you’re good to go.

This basic concept is somewhat similar to Amazon’s Proteus robot, in the sense that you can have one smart powered base that moves around a bunch of less smart and unpowered payloads by driving underneath them and then carrying them around. But SwitchBot’s payloads aren’t just passive cargo, and the base can provide them with a useful amount of power.

A power port allows you to develop your own payloads for the robot.SwitchBot

SwitchBot is actively encouraging users to “to create, adapt, and personalize the robot for a wide variety of innovative applications,” which may include “3D-printed components [or] third-party devices with multiple power ports for speakers, car fridges, or even UV sterilization lamps,” according to the press release. The maximum payload is only 8 kilograms, though, so don’t get too crazy.

Several SwitchBots can make bath time much more enjoyable.SwitchBot

What we all want to know is when someone will put an arm on this thing, and SwitchBot is of course already working on this:

SwitchBot’s mobile manipulator is still in the lab stage.SwitchBot

The arm is still “in the lab stage,” SwichBot says, which I’m guessing means that the hardware is functional but that getting it to reliably do useful stuff with the arm is still a work in progress. But that’s okay—getting an arm to reliably do useful stuff is a work in progress for all of robotics, pretty much. And if SwitchBot can manage to produce an affordable mobile manipulation platform for consumers that even sort of works, that’ll be very impressive.

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.

Enjoy today’s videos!

It’s me. But we can all relate to this child android robot struggling to stay awake.

[ Osaka University ]

[ Team B-Human ]

[ Imperial College London ]

Thanks, Digby!

[ Zarrouk Lab ]

[ Franka Robotics ]

Aldebaran has sold an astonishing number of robots this year.

[ Aldebaran ]

[ Ailos Robotics ]

[ MAVRL via Github ]

[ Personal Robotics Lab ]

A drone’s eye-view reminder that fireworks explode in 3D.

[ Team BlackSheep ]

The future of human habitation in the sea is taking shape in an abandoned quarry on the border of Wales and England. There, the ocean-exploration organization Deep has embarked on a multiyear quest to enable scientists to live on the seafloor at depths up to 200 meters for weeks, months, and possibly even years.

“Aquarius Reef Base in St. Croix was the last installed habitat back in 1987, and there hasn’t been much ground broken in about 40 years,” says Kirk Krack, human diver performance lead at Deep. “We’re trying to bring ocean science and engineering into the 21st century.”

This article is part of our special report Top Tech 2025.

Deep’s agenda has a major milestone this year—the development and testing of a small, modular habitat called Vanguard. This transportable, pressurized underwater shelter, capable of housing up to three divers for periods ranging up to a week or so, will be a stepping stone to a more permanent modular habitat system—known as Sentinel—that is set to launch in 2027. “By 2030, we hope to see a permanent human presence in the ocean,” says Krack. All of this is now possible thanks to an advanced 3D printing-welding approach that can print these large habitation structures.

How would such a presence benefit marine science? Krack runs the numbers for me: “With current diving at 150 to 200 meters, you can only get 10 minutes of work completed, followed by 6 hours of decompression. With our underwater habitats we’ll be able to do seven years’ worth of work in 30 days with shorter decompression time. More than 90 percent of the ocean’s biodiversity lives within 200 meters’ depth and at the shorelines, and we only know about 20 percent of it.” Understanding these undersea ecosystems and environments is a crucial piece of the climate puzzle, he adds: The oceans absorb nearly a quarter of human-caused carbon dioxide and roughly 90 percent of the excess heat generated by human activity.

Deep is looking to build an underwater life-support infrastructure that features not just modular habitats but also training programs for the scientists who will use them. Long-term habitation underwater involves a specialized type of activity called saturation diving, so named because the diver’s tissues become saturated with gases, such as nitrogen or helium. It has been used for decades in the offshore oil and gas sectors but is uncommon in scientific diving, outside of the relatively small number of researchers fortunate enough to have spent time in Aquarius. Deep wants to make it a standard practice for undersea researchers.

The first rung in that ladder is Vanguard, a rapidly deployable, expedition-style underwater habitat the size of a shipping container that can be transported and supplied by a ship and house three people down to depths of about 100 meters. It is set to be tested in a quarry outside of Chepstow, Wales, in the first quarter of 2025.

The Vanguard habitat, seen here in an illustrator’s rendering, will be small enough to be transportable and yet capable of supporting three people at a maximum depth of 100 meters.Deep

The plan is to be able to deploy Vanguard wherever it’s needed for a week or so. Divers will be able to work for hours on the seabed before retiring to the module for meals and rest.

One of the novel features of Vanguard is its extraordinary flexibility when it comes to power. There are currently three options: When deployed close to shore, it can connect by cable to an onshore distribution center using local renewables. Farther out at sea, it could use supply from floating renewable-energy farms and fuel cells that would feed Vanguard via an umbilical link, or it could be supplied by an underwater energy-storage system that contains multiple batteries that can be charged, retrieved, and redeployed via subsea cables.

The breathing gases will be housed in external tanks on the seabed and contain a mix of oxygen and helium that will depend on the depth. In the event of an emergency, saturated divers won’t be able to swim to the surface without suffering a life-threatening case of decompression illness. So, Vanguard, as well as the future Sentinel, will also have backup power sufficient to provide 96 hours of life support, in an external, adjacent pod on the seafloor.

Data gathered from Vanguard this year will help pave the way for Sentinel, which will be made up of pods of different sizes and capabilities. These pods will even be capable of being set to different internal pressures, so that different sections can perform different functions. For example, the labs could be at the local bathymetric pressure for analyzing samples in their natural environment, but alongside those a 1-atmosphere chamber could be set up where submersibles could dock and visitors could observe the habitat without needing to equalize with the local pressure.

As Deep sees it, a typical configuration would house six people—each with their own bedroom and bathroom. It would also have a suite of scientific equipment including full wet labs to perform genetic analyses, saving days by not having to transport samples to a topside lab for analysis.

“By 2030, we hope to see a permanent human presence in the ocean,” says one of the project’s principals

A Sentinel configuration is designed to go for a month before needing a resupply. Gases will be topped off via an umbilical link from a surface buoy, and food, water, and other supplies would be brought down during planned crew changes every 28 days.

But people will be able to live in Sentinel for months, if not years. “Once you’re saturated, it doesn’t matter if you’re there for six days or six years, but most people will be there for 28 days due to crew changes,” says Krack.

It’s a very ambitious vision, and Deep has concluded that it can be achieved only with advanced manufacturing techniques. Deep’s manufacturing arm, Deep Manufacturing Labs (DML), has come up with an innovative approach for building the pressure hulls of the habitat modules. It’s using robots to combine metal additive manufacturing with welding in a process known as wire-arc additive manufacturing. With these robots, metal layers are built up as they would be in 3D printing, but the layers are fused together via welding using a metal-inert-gas torch.

At Deep’s base of operations at a former quarry in Tidenham, England, resources include two Triton 3300/3 MK II submarines. One of them is seen here at Deep’s floating “island” dock in the quarry. Deep

During a tour of the DML, Harry Thompson, advanced manufacturing engineering lead, says, “We sit in a gray area between welding and additive process, so we’re following welding rules, but for pressure vessels we [also] follow a stress-relieving process that is applicable for an additive component. We’re also testing all the parts with nondestructive testing.”

Each of the robot arms has an operating range of 2.8 by 3.2 meters, but DML has boosted this area by means of a concept it calls Hexbot. It’s based on six robotic arms programmed to work in unison to create habitat hulls with a diameter of up to 6.1 meters. The biggest challenge with creating the hulls is managing the heat during the additive process to keep the parts from deforming as they are created. For this, DML is relying on the use of heat-tolerant steels and on very precisely optimized process parameters.

Besides manufacturing, there are other challenges that are unique to the tricky business of keeping people happy and alive 200 meters underwater. One of the most fascinating of these revolves around helium. Because of its narcotic effect at high pressure, nitrogen shouldn’t be breathed by humans at depths below about 60 meters. So, at 200 meters, the breathing mix in the habitat will be 2 percent oxygen and 98 percent helium. But because of its very high thermal conductivity, “we need to heat helium to 31–32 °C to get a normal 21–22 °C internal temperature environment,” says Rick Goddard, director of engineering at Deep. “This creates a humid atmosphere, so porous materials become a breeding ground for mold”.

There are a host of other materials-related challenges, too. The materials can’t emit gases, and they must be acoustically insulating, lightweight, and structurally sound at high pressures.

Deep’s proving grounds are a former quarry in Tidenham, England, that has a maximum depth of 80 meters. Deep

There are also many electrical challenges. “Helium breaks certain electrical components with a high degree of certainty,” says Goddard. “We’ve had to pull devices to pieces, change chips, change [printed circuit boards], and even design our own PCBs that don’t off-gas.”

The electrical system will also have to accommodate an energy mix with such varied sources as floating solar farms and fuel cells on a surface buoy. Energy-storage devices present major electrical engineering challenges: Helium seeps into capacitors and can destroy them when it tries to escape during decompression. Batteries, too, develop problems at high pressure, so they will have to be housed outside the habitat in 1-atmosphere pressure vessels or in oil-filled blocks that prevent a differential pressure inside.

When you’re trying to be the SpaceX of the ocean, questions are naturally going to fly about the feasibility of such an ambition. How likely is it that Deep can follow through? At least one top authority, John Clarke, is a believer. “I’ve been astounded by the quality of the engineering methods and expertise applied to the problems at hand and I am enthusiastic about how DEEP is applying new technology,” says Clarke, who was lead scientist of the U.S. Navy Experimental Diving Unit. “They are advancing well beyond expectations…. I gladly endorse Deep in their quest to expand humankind’s embrace of the sea.”

2024 was the best year ever for robotics, which I’m pretty sure is not something that I’ve ever said before. But that’s the great thing about robotics—it’s always new, and it’s always exciting. What may be different about this year is the real sense that not only is AI going to change everything about robots, but that it will somehow make robots useful and practical and commercially viable. Is that true? Nobody knows yet! But it means that 2025 might actually be the best year ever for robotics, if you’ve ever wanted a robot to help you out at home or at work.

So as we look forward to 2025, here are some of our most interesting and impactful stories of the past year. And as always, thanks for reading!

Figure

This announcement from back in February is pretty much what set the tone for robotics in 2024. Figure’s Series B raise valued the company at a bonkers US $2.6 billion, and all of a sudden, humanoids were where it’s at. And by “it,” I mean everything, from funding to talent to breathless media coverage. The big question of 2024 was whether or not humanoids would be able to deliver on their promises, and that’s shaping up to be the big question of 2025, too.

Boston Dynamics

It didn’t take long for legendary robotics company Boston Dynamics to make it clear that they’re not going to be left behind when it comes to commercial humanoids. For a company that has been leading humanoid research longer than just about anyone but has bounced around from owner to owner over the last 10 years, we were a little unsure whether Atlas would ever be more than a research platform. But the new all-electric Atlas is designed for work, and we saw it get busy in 2024.

Boston Dynamics

As much as we’re excited for the new Atlas, the old hydraulic Atlas will always have a special place in our hearts. We’ve been through so much together, from the DRC to parkour to dancing. Electric robots are great and all, and I understand why they’re necessary for commercial applications, but all of that hydraulic power meant that hydraulic Atlas was able to move in dynamic ways that we may not see again for a very long time.

Nvidia

So we’ve got all these humanoid robots now with all this impressive hardware, but the really hard part (or one of them, anyway) is getting those robots to actually do something commercially useful in a safe and reliable way. Is training in simulation the answer? I don’t know, but NVIDIA sure thinks so, and they’ve made a huge commitment by investing in GR00T, a “general-purpose foundation model for humanoid robots.” And what does that mean, exactly? Nobody’s quite sure yet, but with NVIDIA behind it that’s enough to make the entire industry pay attention.

Evan Ackerman

With all the attention on humanoid robots right now, it’s critical to be able to separate real progress from hype. Unfortunately, there are all kinds of ways of cheating with robots. And there’s really nothing wrong with cheating with robots, as long as you tell people that the cheating is happening, and then (hopefully) cheat less and less as your robot gets better and better. In particular, we’re likely to see more and more teleoperation of humanoid robots (obviously or otherwise) because that’s one of the best ways of collecting training data: by having a human do it. And being able to tell that a human is doing it is an important skill to have.

Machina Labs

Some of my favorite robots are robots that are able to leverage their robotic-ness to not just do things that humans do, but also do things that humans cannot do. Robots have the patience and precision to work metal in ways that a very highly skilled human might be able to do once, but the robots (being robots) can do it over and over again. NASA is leveraging this capability to build complex toroidal tanks for spacecraft, but it has the potential to change anything that’s made out of sheet metal.

JPL-Caltech/ASU/NASA

One of the greatest robotics stories of the last several years has been Ingenuity, the little Mars helicopter. We’ve written extensively about how Ingenuity was designed, how it can fly on Mars, and how it just kept on flying, more than 50 times. But it couldn’t fly forever, and as Ingenuity was pushed to fly farther and farther over more challenging terrain, flight 72 was to be its last. After losing its ability to localize over some particularly featureless terrain, the little robot had a very rough landing. It lived to tell the tale, but not to fly again.

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.

Enjoy today’s videos!

Yours for US $100,000.

[ Unitree ]

Yes I know we’re sharing some of these holiday videos are a little late, but I deserve a little bit of time off, don’t I? No, you’re right, and I feel shame. But please enjoy these extra holiday videos anyway, starting with Santa’s Little Helper from ETHZ RSL.

Okay but seriously where do I get one of those little plush Anymals!

[ RSL ]

Merry Christmas from the Kepler humanoid robot!

[ Kepler Robotics ]

[ Flexiv ]

[ IHMC ]

Thanks, Robert!

[ PAL Robotics ]

[ DARPA ]

[ Innate ]

[ Norwegian University of Science and Technology post on LinkedIn ]

Thanks, Kostas!

[ Robot Era ]

Thanks, Ni Tao!

[ Osaka University ]

[ Paper via IEEE Robotics and Automation magazine in IEEE Xplore ]

[ Guillaume Loquin ] via [ Engadget ]

This is a big deal.

[ Ekso Bionics ]

[ Sanctuary AI ]

[ Pudu Robotics ]

[ EngineAI ]

[ Cybathlon ]

At the Kanda Myoujin Shrine in Tokyo, Aibos and their owners take part in the Shichi-go-san festival, which celebrates children (and robots!) at 3, 5, and 7 years old.

[ Aibo ]

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.

Enjoy today’s videos!

[ FZI ]

Thanks, Georg!

[ Fraunhofer IOSB ]

Thanks, Janko!

There’s some thrilling action in this Christmas video from the PUT Mobile Robotics Laboratory, and the trick to put the lights on the tree is particularly clever. Enjoy!

[ PUT MRL ]

Thanks, Dominik!

[ Northern Robotics Laboratory ]

The Learning Systems and Robotics Lab has made a couple of robot holiday videos based on the research that they’re doing:

[ Crowd Navigation ]

[ Learning with Contacts ]

Thanks, Sepehr!

[ DFKI ]

[ Clearpath Robotics ]

[ PAL Robotics ]

Thanks, Rugilė!

[ ArtiMinds ]

[ FANUC ]

Perhaps not technically a holiday video, until you consider how all that stuff you ordered online is actually getting to you.

[ Agility Robotics ]

[ Quanser ]

[ Kawasaki Robotics ]

The robotics students at Queen’s University’s Ingenuity Labs Research Institute put together a 4K Holiday Robotics Lab Fireplace video, and unlike most fireplace videos, stuff actually happens in this one.

[ Ingenuity Labs ]

Thanks, Joshua!

This is a sponsored article brought to you by Amazon.

Innovation often begins as a spark of an idea—a simple “what if” that grows into something transformative. But turning that spark into a fully realized solution requires more than just ingenuity. It requires resources, collaboration, and a relentless drive to bridge the gap between concept and execution. At Amazon, these ingredients come together to create breakthroughs that not only solve today’s challenges but set the stage for the future.

“Innovation doesn’t just happen because you have a good idea,” said Valerie Samzun, a leader in Amazon’s Fulfillment Technologies and Robotics (FTR) division. “It happens because you have the right team, the right resources, and the right environment to bring that idea to life.”

This philosophy underpins Amazon’s approach to robotics, exemplified by Robin, a groundbreaking robotic system designed to tackle some of the most complex logistical challenges in the world. Robin’s journey, from its inception to deployment in fulfillment centers worldwide, offers a compelling look at how Amazon fosters innovation at scale.

Amazon’s fulfillment centers handle millions of items daily, each destined for a customer expecting precision and speed. The scale and complexity of these operations are unparalleled. Items vary widely in size, shape, and weight, creating an unpredictable and dynamic environment where traditional robotic systems often falter.

“Robots are great at consistency,” Jason Messinger, robotics senior manager explained. “But what happens when every task is different? That’s the reality of our fulfillment centers. Robin had to be more than precise—it had to be adaptable.”

Robin was designed to pick and sort items with speed and accuracy, but its capabilities extend far beyond basic functionality. The system integrates cutting-edge technologies in artificial intelligence, computer vision, and mechanical engineering to learn from its environment and improve over time. This ability to adapt was crucial for operating in fulfillment centers, where no two tasks are ever quite the same.

“When we designed Robin, we weren’t building for perfection in a lab,” Messinger said. “We were building for the chaos of the real world. That’s what makes it such an exciting challenge.”

Robin’s development was a collaborative effort involving teams of roboticists, data scientists, mechanical engineers, and operations specialists. This multidisciplinary approach allowed the team to address every aspect of Robin’s performance, from the algorithms powering its decision-making to the durability of its mechanical components.

“Robin is more than a robot. It’s a learning system. Every pick makes it smarter, faster, and better.” —Valerie Samzun, Amazon

“At Amazon, you don’t work in silos,” both Messinger and Samzun noted. Samzun continued, “every problem is tackled from multiple angles, with input from people who understand the technology, the operations, and the end user. That’s how you create something that truly works.”

This collaboration extended to testing and deployment. Robin was not confined to a controlled environment but was tested in live settings that replicated the conditions of Amazon’s fulfillment centers. Engineers could see Robin in action, gather real-time data, and refine the system iteratively.

“Every deployment teaches us something,” Messinger said. “Robin didn’t just evolve on paper—it evolved in the field. That’s the power of having the resources and infrastructure to test at scale.”

For many of the engineers and researchers involved in Robin’s development, the opportunity to work at Amazon represented a significant shift from their previous experiences. Unlike academic settings, where projects often remain theoretical, or smaller companies, where resources may be limited, Amazon offers the scale, speed, and impact that few other organizations can match.

Learn more about becoming part of Amazon’s Team →

“One of the things that drew me to Amazon was the chance to see my work in action,” said Megan Mitchell, who leads a team of manipulation hardware and systems engineers for Amazon Robotics. “Working in R&D, I spent years exploring novel concepts, but usually didn’t get to see those translate to the real world. At Amazon, I get to take ideas to the field in a matter of months.”

This sense of purpose is a recurring theme among Amazon’s engineers. The company’s focus on creating solutions that have a tangible impact—on operations, customers, and the industry as a whole—resonates with those who want their work to matter.

“At Amazon, you’re not just building technology—you’re building the future,” Mitchell said. “That’s an incredibly powerful motivator. You know that what you’re doing isn’t just theoretical—it’s making a difference.”

In addition to the impact of their work, engineers at Amazon benefit from access to unparalleled resources. From state-of-the-art facilities to vast amounts of real-world data, Amazon provides the tools necessary to tackle even the most complex challenges.

“If you need something to make the project better, Amazon makes it happen. That’s a game-changer,” said Messinger.

The culture of collaboration and iteration is another draw. Engineers at Amazon are encouraged to take risks, experiment, and learn from failure. This iterative approach not only accelerates innovation but also creates an environment where creativity thrives.

During its development, Robin was not confined to a controlled environment but was tested in live settings that replicated the conditions of Amazon’s fulfillment centers. Engineers could see Robin in action, gather real-time data, and refine the system iteratively.Amazon

Since its deployment, Robin has revolutionized operations in Amazon’s fulfillment centers. The robot has performed billions of picks, demonstrating reliability, adaptability, and efficiency. Each item it handles provides valuable data, allowing the system to continuously improve.

“Robin is more than a robot,” Samzun said. “It’s a learning system. Every pick makes it smarter, faster, and better.”

Robin’s impact extends beyond efficiency. By taking over repetitive and physically demanding tasks, the system has improved safety for Amazon’s associates. This has been a key priority for Amazon, which is committed to creating a safe and supportive environment for its workforce.

“When Robin picks an item, it’s not just about speed or accuracy,” Samzun explained. “It’s about making the workplace safer and the workflow smoother. That’s a win for everyone.”

Robin’s success is just the beginning. The lessons learned from its development are shaping the future of robotics at Amazon, paving the way for even more advanced systems. These innovations will not only enhance operations but also set new standards for what robotics can achieve.

“At Amazon, you feel like you’re a part of something bigger. You’re not just solving problems—you’re creating solutions that matter.” —Jason Messinger, Amazon

“This isn’t just about one robot,” Mitchell said. “It’s about building a platform for continuous innovation. Robin showed us what’s possible, and now we’re looking at how to go even further.”

For the engineers and researchers involved, Robin’s journey has been transformative. It has provided an opportunity to work on cutting-edge technology, solve complex problems, and make a meaningful impact—all while being part of a team that values creativity and collaboration.

“At Amazon, you feel like you’re a part of something bigger,” said Messinger. “You’re not just solving problems—you’re creating solutions that matter.”

Robin’s story is a testament to the power of ambition, collaboration, and execution. It demonstrates that with the right resources and mindset, even the most complex challenges can be overcome. But more than that, it highlights the unique role Amazon plays in shaping the future of robotics and logistics.

“Innovation isn’t just about having a big idea,” Samzun said. “It’s about turning that idea into something real, something that works, and something that makes a difference. That’s what Robin represents, and that’s what we do every day at Amazon.”

Robin isn’t just a robot—it’s a symbol of what’s possible when brilliant minds come together to solve real-world problems. As Amazon continues to push the boundaries of what robotics can achieve, Robin’s legacy will be felt in every pick, every delivery, and every step toward a more efficient and connected future.

Learn more about becoming part of Amazon’s Team.

The Modified Agile for Hardware Development (MAHD) Framework is the ultimate solution for hardware teams seeking the benefits of Agile without the pitfalls of applying software-centric methods. Traditional development approaches, like waterfall, often result in delayed timelines, high risks, and misaligned priorities. Meanwhile, software-based Agile frameworks fail to account for hardware's complexity. MAHD resolves these challenges with a tailored process that blends Agile principles with hardware-specific strategies.

Central to MAHD is its On-ramp process, a five-step method designed to kickstart projects with clarity and direction. Teams define User Stories to capture customer needs, outline Product Attributes to guide development, and use the Focus Matrix to link solutions to outcomes. Iterative IPAC cycles, a hallmark of the MAHD Framework, ensure risks are addressed early and progress is continuously tracked. These cycles emphasize integration, prototyping, alignment, and customer validation, providing structure without sacrificing flexibility.

MAHD has been successfully implemented across diverse industries, from medical devices to industrial automation, delivering products up to 50% faster while reducing risk. For hardware teams ready to adopt Agile methods that work for their unique challenges, this ebook provides the roadmap to success.

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.

Enjoy today’s videos!

We wrote an article about an earlier concept version of this thing a few years back if you’d like more detail about it.

[ NASA ]

[ Sanctuary AI ]

[ Clone Robotics ]

[ Suzumori Endo Lab ]

[ LucidSim ]

[ Science Robotics ]

[ Paper authors from University of Leeds and University College London ]

Thanks, Chengxu!

Happy 60th birthday to MIT CSAIL!

[ MIT Computer Science and Artificial Intelligence Laboratory ]

Yup, humanoid progress can move quickly when you put your mind to it.

[ MagicLab ]

[ Sung Robotics Lab ]

From now on I will open doors like the robot in this video.

[ Humanoids 2024 ]

[ NASA ]

Our time is limited when it comes to flying drones, but we haven’t been surpassed by AI yet.

[ Team BlackSheep ]

Daniele Pucci from IIT discusses iCub and ergoCub as part of the industrial panel at Humanoids 2024.

[ ergoCub ]