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The Ingenuity Mars Helicopter made its 72nd and final flight on 18 January. “While the helicopter remains upright and in communication with ground controllers,” NASA’s Jet Propulsion Lab said in a press release this afternoon, “imagery of its Jan. 18 flight sent to Earth this week indicates one or more of its rotor blades sustained damage during landing, and it is no longer capable of flight.” That’s what you’re seeing in the picture above: the shadow of a broken tip of one of the helicopter’s four two-foot long carbon fiber rotor blades. NASA is assuming that at least one blade struck the Martian surface during a “rough landing,” and this is not the kind of damage that will allow the helicopter to get back into the air. Ingenuity’s mission is over.


The Perseverance rover took this picture of Ingenuity on on Aug. 2, 2023, just before flight 54.NASA/JPL-Caltech/ASU/MSSS

NASA held a press conference earlier this evening to give as much information as they can about exactly what happened to Ingenuity, and what comes next. First, here’s a summary from the press release:

Ingenuity’s team planned for the helicopter to make a short vertical flight on Jan. 18 to determine its location after executing an emergency landing on its previous flight. Data shows that, as planned, the helicopter achieved a maximum altitude of 40 feet (12 meters) and hovered for 4.5 seconds before starting its descent at a velocity of 3.3 feet per second (1 meter per second).

However, about 3 feet (1 meter) above the surface, Ingenuity lost contact with the rover, which serves as a communications relay for the rotorcraft. The following day, communications were reestablished and more information about the flight was relayed to ground controllers at NASA JPL. Imagery revealing damage to the rotor blade arrived several days later. The cause of the communications dropout and the helicopter’s orientation at time of touchdown are still being investigated.

While NASA doesn’t know for sure what happened, they do have some ideas based on the cause of the emergency landing during the previous flight, Flight 71. “[This location] is some of the hardest terrain we’ve ever had to navigate over,” said Teddy Tzanetos, Ingenuity Project Manager at NASA JPL, during the NASA press conference. “It’s very featureless—bland, sandy terrain. And that’s why we believe that during Flight 71, we had an emergency landing. She was flying over the surface and was realizing that there weren’t too many rocks to look at or features to navigate from, and that’s why Ingenuity called an emergency landing on her own.”

Ingenuity uses a downward-pointing VGA camera running at 30hz for monocular feature tracking, and compares the apparent motion of distinct features between frames to determine its motion over the ground. This optical flow technique is used for drones (and other robots) on Earth too, and it’s very reliable, as long as you have enough features to track. Where it starts to go wrong is when your camera is looking at things that are featureless, which is why consumer drones will sometimes warn you about unexpected behavior when flying over water, and why robotics labs often have bizarre carpets and wallpaper: the more features, the better. On Mars, Ingenuity has been reliably navigating by looking for distinctive features like rocks, but flying over a featureless expanse of sand caused serious problems, as Ingenuity’s Chief Pilot Emeritus Håvard Grip explained to us during today’s press conference:

The way a system like this works is by looking at the consensus of [the features] it sees, and then throwing out the things that don’t really agree with the consensus. The danger is when you run out of features, when you don’t have very many features to navigate on, and you’re not really able to establish what that consensus is and you end up tracking the wrong kinds of features, and that’s when things can get off track.

This view from Ingenuity’s navigation camera during flight 70 (on December 22) shows areas of nearly featureless terrain that would cause problems during flights 71 and 72.NASA/JPL-Caltech

After the Flight 71 emergency landing, the team decided to try a “pop-up” flight next: it was supposed to be about 30 seconds in the air, just straight up to 12 meters and then straight down as a check-out of the helicopter’s systems. As Ingenuity was descending, just before landing, there was a loss of communications with the helicopter. “We have reason to believe that it was facing the same featureless sandy terrain challenges [as in the previous flight],” said Tzanetos. “And because of the navigation challenges, we had a rotor strike with the surface that would have resulted in a power brownout which caused the communications loss.” Grip describes what he thinks happened in more detail:

Some of this is speculation because of the sparse telemetry that we have, but what we see in the telemetry is that coming down towards the last part of the flight, on the sand, when we’re closing in on the ground, the helicopter relatively quickly starts to think that it’s moving horizontally away from the landing target. It’s likely that it made an aggressive maneuver to try to correct that right upon landing. And that would have accounted for a sideways motion and tilt of the helicopter that could have led to either striking the blade to the ground and then losing power, or making a maneuver that was aggressive enough to lose power before touching down and striking the blade, we don’t know those details yet. We may never know. But we’re trying as hard as we can with the data that we have to figure out those details.

When the Ingenuity team tried reestablishing contact with the helicopter the next sol, “she was right there where we expected her to be,” Tzanetos said. “Solar panel currents were looking good, which indicated that she was upright.” In fact, everything was “green across the board.” That is, until the team started looking through the images from Ingenuity’s navigation camera, and spotted the shadow of the damaged lower blade. Even if that’s the only damage to Ingenuity, the whole rotor system is now both unbalanced and producing substantially less lift, and further flights will be impossible.

A closeup of the shadow of the damaged blade tip.NASA/JPL-Caltech

There’s always that piece in the back of your head that’s getting ready every downlink—today could be the last day, today could be the last day. So there was an initial moment, obviously, of sadness, seeing that photo come down and pop on screen, which gives us certainty of what occurred. But that’s very quickly replaced with happiness and pride and a feeling of celebration for what we’ve pulled off. Um, it’s really remarkable the journey that she’s been on and worth celebrating every single one of those sols. Around 9pm tonight Pacific time will mark 1000 sols that Ingenuity has been on the surface since her deployment from the Perseverance rover. So she picked a very fitting time to come to the end of her mission. —Teddy Tzanetos

The Ingenuity team is guessing that there’s damage to more than one of the helicopter’s blades; the blades spin fast enough that if one hit the surface, others likely did too. The plan is to attempt to slowly spin the blades to bring others into view to try and collect more information. It sounds unlikely that NASA will divert the Perseverance rover to give Ingenuity a closer look; while continuing on its sincere mission the rover will come between 200 and 300 meters of Ingenuity and will try to take some pictures, but that’s likely too far away for a good quality image.

Perseverance watches Ingenuity take off on flight 47 on March 14, 2023.NASA/JPL-Caltech/ASU/MSSS

As a tech demo, Ingenuity’s entire reason for existence was to push the boundaries of what’s possible. And as Grip explains, even in its last flight, the little helicopter was doing exactly that, going above and beyond and trying newer and riskier things until it got as far as it possibly could:

Overall, the way that Ingenuity has navigated using features of terrain has been incredibly successful. We didn’t design this system to handle this kind of terrain, but nonetheless it’s sort of been invincible until this moment where we flew in this completely bland terrain where you just have nothing to really hold on to. So there are some lessons in that for us: we now know that that particular kind of terrain can be a trap for a system like this. Backing up when encountering this featureless terrain is a functionality that a future helicopter could be equipped with. And then there are solutions like having a higher resolution camera, which would have likely helped mitigate this situation. But it’s all part of this tech demo, where we equipped this helicopter to do at most five flights in a pre-scouted area and it’s gone on to do so much more than that. And we just worked it all the way up to the line, and then just tipped it right over the line to where it couldn’t handle it anymore.

Arguably, Ingenuity’s most important contribution has been showing that it’s not just possible, but practical and valuable to have rotorcraft on Mars. “I don’t think we’d be talking about sample recovery helicopters if Ingenuity didn’t fly, period, and if it hadn’t survived for as long as it has,” Teddy Tzanetos told us after Ingenuity’s 50th flight. And it’s not just the sample return mission: JPL is also developing a much larger Mars Science Helicopter, which will owe its existence to Ingenuity’s success.

Nearly three years on Mars. 128 minutes and 11 miles of flight in the Martian skies. “I look forward to the day that one of our astronauts brings home Ingenuity and we can all visit it in the Smithsonian,” said Director of JPL Laurie Leshin at the end of today’s press conference.

I’ll be first in line.

We’ve written extensively about Ingenuity, including in-depth interviews with both helicopter and rover team members, and they’re well worth re-reading today. Thanks, Ingenuity. You did well.


What Flight 50 Means for the Ingenuity Mars Helicopter

Team lead Teddy Tzanetos on the helicopter’s milestone aerial mission


Mars Helicopter Is Much More Than a Tech Demo

A Mars rover driver explains just how much of a difference the little helicopter scout is making to Mars exploration


Ingenuity’s Chief Pilot Explains How to Fly a Helicopter on Mars

Simulation is the secret to flying a helicopter on Mars


How NASA Designed a Helicopter That Could Fly Autonomously on Mars

The Perseverance rover’s Mars Helicopter (Ingenuity) will take off, navigate, and land on Mars without human intervention

A planetary exploration rover has been employed for scientific endeavors or as a precursor for upcoming manned missions. Predicting rover traversability from its wheel slip ensures safe and efficient autonomous operations of rovers on deformable planetary surfaces; path planning algorithms that reduce slips by considering wheel-soil interaction or terrain data can minimize the risk of the rover becoming immobilized. Understanding wheel-soil interaction in transient states is vital for developing a more precise slip ratio prediction model, while path planning in the past assumes that slips generated at the path is a series of slip ratio in steady state. In this paper, we focus on the transient slip, or slip rate the time derivative of slip ratio, to explicitly address it into the cost function of path planning algorithm. We elaborated a regression model that takes slip rate and traction force as inputs and outputs slip ratio, which is employed in the cost function to minimize the rover slip in path planning phase. Experiments using a single wheel testbed revealed that even with the same wheel traction force, the slip ratio varies with different slip rates; we confirmed that the smaller the absolute value of the slip rate, the larger the slip ratio for the same traction force. The statistical analysis of the regression model confirms that the model can estimate the slip ratio within an accuracy of 85% in average. The path planning simulation with the regression model confirmed a reduction of 58% slip experienced by the rover when driving through rough terrain environments. The dynamics simulation results insisted that the proposed method can reduce the slip rate in rough terrain environments.

Active upper limb exoskeletons are a potentially powerful tool for neuromotor rehabilitation. This potential depends on several basic control modes, one of them being transparency. In this control mode, the exoskeleton must follow the human movement without altering it, which theoretically implies null interaction efforts. Reaching high, albeit imperfect, levels of transparency requires both an adequate control method and an in-depth evaluation of the impacts of the exoskeleton on human movement. The present paper introduces such an evaluation for three different “transparent” controllers either based on an identification of the dynamics of the exoskeleton, or on force feedback control or on their combination. Therefore, these controllers are likely to induce clearly different levels of transparency by design. The conducted investigations could allow to better understand how humans adapt to transparent controllers, which are necessarily imperfect. A group of fourteen participants were subjected to these three controllers while performing reaching movements in a parasagittal plane. The subsequent analyses were conducted in terms of interaction efforts, kinematics, electromyographic signals and ergonomic feedback questionnaires. Results showed that, when subjected to less performing transparent controllers, participants strategies tended to induce relatively high interaction efforts, with higher muscle activity, which resulted in a small sensitivity of kinematic metrics. In other words, very different residual interaction efforts do not necessarily induce very different movement kinematics. Such a behavior could be explained by a natural human tendency to expend effort to preserve their preferred kinematics, which should be taken into account in future transparent controllers evaluation.



Over the past few weeks, we’ve seen a couple of high-profile videos of robotic systems doing really impressive things. And I mean, that’s what we’re all here for, right? Being impressed by the awesomeness of robots! But sometimes the awesomeness of robots is more complicated than what you see in a video making the rounds on social media—any robot has a lot of things going on behind the scenes to make it successful, but if you can’t tell what those things are, what you see at first glance might be deceiving you.

Earlier this month, a group of researchers from Stanford’s IRIS Lab introduced Mobile ALOHA, which (if you read the YouTube video description) is described as “a low-cost and whole-body teleoperation system for data collection”:

And just last week, Elon Musk posted a video of Tesla’s Optimus robot folding a shirt:

— (@)

Most people who watch these videos without poking around in the descriptions or comments will likely not assume that these robots were being entirely controlled by experienced humans, because why would they? Even for roboticists, it can be tricky to know for sure whether the robot they’re watching has a human in the loop somewhere. This is a problem that’s not unique to the folks behind either of the videos above; it’s a communication issue that the entire robotics community struggles with. But as robots (and robot videos) become more mainstream, it’s important that we get better at it.

Why use teleoperation?

Humans are way, way, way, way, way better than robots at almost everything. We’re fragile and expensive, which is why so many people are trying to get robots to do stuff instead, but with a very few exceptions involving speed and precision, humans are the gold standard and are likely to remain so for the foreseeable future. So, if you need a robot to do something complicated or something finicky or something that might require some innovation or creativity, the best solution is to put a human in control.

What about autonomy, though?

Having one-to-one human teleoperation of a robot is a great way of getting things done, but it’s not scalable, and aside from some very specific circumstances, the whole point of robots is to do stuff autonomously at scale so that humans don’t have to. One approach to autonomy is to learn as much as you can from human teleoperation: Many robotics companies are betting that they’ll be able to use humans to gradually train their robotic systems, transitioning from full teleoperation to partial teleoperation to supervisory control to full autonomy. Sanctuary AI is a great example of this: They’ve been teleoperating their humanoid robots through all kinds of tasks, collecting training data as a foundation for later autonomy.

What’s wrong with teleoperation, then?

Nothing! Teleoperation is great. But when people see a robot doing something and it looks autonomous but it’s actually teleoperated, that’s a problem, because it’s a misrepresentation of the state of the technology. Not only do people end up with the wrong idea of how your robot functions and what it’s really capable of, it also means that whenever those people see other robots doing similar tasks autonomously, their frame of reference will be completely wrong, minimizing what otherwise may be a significant contribution to the field by other robotics folks. To be clear, I don’t (usually) think that the roboticists making these videos have any intention of misleading people, but that is unfortunately what often ends up happening.

What can we do about this problem?

Last year, I wrote an article for the IEEE Robotics & Automation Society (RAS) with some tips for making a good robot video, which includes arguably the most important thing: context. This covers teleoperation, along with other common things that can cause robot videos to mislead an unfamiliar audience. Here’s an excerpt from the RAS article:

It’s critical to provide accurate context for videos of robots. It’s not always clear (especially to nonroboticists) what a robot may be doing or not doing on its own, and your video should be as explicit as possible about any assistance that your system is getting. For example, your video should identify:

  • If the video has been sped up or slowed down
  • If the video makes multiple experiments look like one continuous experiment
  • If external power, compute, or localization is being used
  • How the robot is being controlled (e.g., human in the loop, human supervised, scripted actions, partial autonomy, full autonomy)

These things should be made explicit on the video itself, not in the video description or in captions. Clearly communicating the limitations of your work is the responsible thing to do, and not doing this is detrimental to the robotics community.

I want to emphasize that context should be made explicit on the video itself. That is, when you edit the video together, add captions or callouts or something that describes the context on top of the actual footage. Don’t put it in the description or in the subtitles or in a link, because when videos get popular online, they may be viewed and shared and remixed without any of that stuff being readily available.

So how can I tell if a robot is being teleoperated?

If you run across a video of a robot doing some kind of amazing manipulation task and aren’t sure whether it’s autonomous or not, here are some questions to ask that might help you figure it out.

  • Can you identify an operator? In both of the videos we mentioned above, if you look very closely, you can tell that there’s a human operator, whether it’s a pair of legs or a wayward hand in a force-sensing glove. This may be the first thing to look for, because sometimes an operator is very obvious, but at the same time, not seeing an operator isn’t particularly meaningful because it’s easy for them to be out of frame.
  • Is there any more information? The second thing to check is whether the video says anywhere what’s actually going on. Does the video have a description? Is there a link to a project page or paper? Are there credits at the end of the video? What account is publishing the video? Even if you can narrow down the institution or company or lab, you might be able to get a sense of whether they’re working on autonomy or teleoperation.
  • What kind of task is it? You’re most likely to see teleoperation in tasks that would be especially difficult for a robot to do autonomously. At the moment, that’s predominantly manipulation tasks that aren’t well structured—for example, getting multiple objects to interact with each other, handling things that are difficult to model (like fabrics), or extended multistep tasks. If you see a robot doing this stuff quickly and well, it’s worth questioning whether it’s autonomous.
  • Is the robot just too good? I always start asking more questions when a robot demo strikes me as just too impressive. But when does impressive become too impressive? Personally, I think a robot demonstrating human-level performance at just about any complex task is too impressive. Some autonomous robots definitely have reached that benchmark, but not many, and the circumstances of them doing so are usually atypical. Furthermore, it takes a lot of work to reach humanlike performance with an autonomous system, so there’s usually some warning in the form of previous work. If you see an impressive demo that comes out of nowhere, showcasing an autonomous capability without any recent precedents, that’s probably too impressive. Remember that it can be tricky with a video because you have no idea whether you’re watching the first take or the 500th, and that itself is a good thing to be aware of—even if it turns out that a demo is fully autonomous, there are many other ways of obfuscating how successful the system actually is.
  • Is it too fast? Autonomous robots are well known for being very fast and precise, but only in the context of structured tasks. For complex manipulation tasks, robots need to sense their environment, decide what to do next, and then plan how to move. This takes time. If you see an extended task that consists of multiple parts but the system never stops moving, that suggests it’s not fully autonomous.
  • Does it move like a human? Robots like to move optimally. Humans might also like to move optimally, but we’re bad at it. Autonomous robots tend to move smoothly and fluidly, while teleoperated robots often display small movements that don’t make sense in the context of the task, but are very humanlike in nature. For example, finger motions that are unrelated to gripping, or returning an arm to a natural rest position for no particular reason, or being just a little bit sloppy in general. If the motions seem humanlike, that’s usually a sign of a human in the loop rather than a robot that’s just so good at doing a task that it looks human.

None of these points make it impossible for an autonomous robot demo to come out of nowhere and blow everyone away. Improbable, perhaps, but not impossible. And the rare moments when that actually happens is part of what makes robotics so exciting. That’s why it’s so important to understand what’s going on when you see a robot doing something amazing, though—knowing how it’s done, and all of the work that went into it, can only make it more impressive.

This article was inspired by Peter Corke‘s LinkedIn post, What’s with all these deceptive teleoperation demos? And extra thanks to Peter for his feedback on an early draft of this article.



Over the past few weeks, we’ve seen a couple of high-profile videos of robotic systems doing really impressive things. And I mean, that’s what we’re all here for, right? Being impressed by the awesomeness of robots! But sometimes the awesomeness of robots is more complicated than what you see in a video making the rounds on social media—any robot has a lot of things going on behind the scenes to make it successful, but if you can’t tell what those things are, what you see at first glance might be deceiving you.

Earlier this month, a group of researchers from Stanford’s IRIS Lab introduced Mobile ALOHA, which (if you read the YouTube video description) is described as “a low-cost and whole-body teleoperation system for data collection”:

And just last week, Elon Musk posted a video of Tesla’s Optimus robot folding a shirt:

— (@)

Most people who watch these videos without poking around in the descriptions or comments will likely not assume that these robots were being entirely controlled by experienced humans, because why would they? Even for roboticists, it can be tricky to know for sure whether the robot they’re watching has a human in the loop somewhere. This is a problem that’s not unique to the folks behind either of the videos above; it’s a communication issue that the entire robotics community struggles with. But as robots (and robot videos) become more mainstream, it’s important that we get better at it.

Why use teleoperation?

Humans are way, way, way, way, way better than robots at almost everything. We’re fragile and expensive, which is why so many people are trying to get robots to do stuff instead, but with a very few exceptions involving speed and precision, humans are the gold standard and are likely to remain so for the foreseeable future. So, if you need a robot to do something complicated or something finicky or something that might require some innovation or creativity, the best solution is to put a human in control.

What about autonomy, though?

Having one-to-one human teleoperation of a robot is a great way of getting things done, but it’s not scalable, and aside from some very specific circumstances, the whole point of robots is to do stuff autonomously at scale so that humans don’t have to. One approach to autonomy is to learn as much as you can from human teleoperation: Many robotics companies are betting that they’ll be able to use humans to gradually train their robotic systems, transitioning from full teleoperation to partial teleoperation to supervisory control to full autonomy. Sanctuary AI is a great example of this: They’ve been teleoperating their humanoid robots through all kinds of tasks, collecting training data as a foundation for later autonomy.

What’s wrong with teleoperation, then?

Nothing! Teleoperation is great. But when people see a robot doing something and it looks autonomous but it’s actually teleoperated, that’s a problem, because it’s a misrepresentation of the state of the technology. Not only do people end up with the wrong idea of how your robot functions and what it’s really capable of, it also means that whenever those people see other robots doing similar tasks autonomously, their frame of reference will be completely wrong, minimizing what otherwise may be a significant contribution to the field by other robotics folks. To be clear, I don’t (usually) think that the roboticists making these videos have any intention of misleading people, but that is unfortunately what often ends up happening.

What can we do about this problem?

Last year, I wrote an article for the IEEE Robotics & Automation Society (RAS) with some tips for making a good robot video, which includes arguably the most important thing: context. This covers teleoperation, along with other common things that can cause robot videos to mislead an unfamiliar audience. Here’s an excerpt from the RAS article:

It’s critical to provide accurate context for videos of robots. It’s not always clear (especially to nonroboticists) what a robot may be doing or not doing on its own, and your video should be as explicit as possible about any assistance that your system is getting. For example, your video should identify:

  • If the video has been sped up or slowed down
  • If the video makes multiple experiments look like one continuous experiment
  • If external power, compute, or localization is being used
  • How the robot is being controlled (e.g., human in the loop, human supervised, scripted actions, partial autonomy, full autonomy)

These things should be made explicit on the video itself, not in the video description or in captions. Clearly communicating the limitations of your work is the responsible thing to do, and not doing this is detrimental to the robotics community.

I want to emphasize that context should be made explicit on the video itself. That is, when you edit the video together, add captions or callouts or something that describes the context on top of the actual footage. Don’t put it in the description or in the subtitles or in a link, because when videos get popular online, they may be viewed and shared and remixed without any of that stuff being readily available.

So how can I tell if a robot is being teleoperated?

If you run across a video of a robot doing some kind of amazing manipulation task and aren’t sure whether it’s autonomous or not, here are some questions to ask that might help you figure it out.

  • Can you identify an operator? In both of the videos we mentioned above, if you look very closely, you can tell that there’s a human operator, whether it’s a pair of legs or a wayward hand in a force-sensing glove. This may be the first thing to look for, because sometimes an operator is very obvious, but at the same time, not seeing an operator isn’t particularly meaningful because it’s easy for them to be out of frame.
  • Is there any more information? The second thing to check is whether the video says anywhere what’s actually going on. Does the video have a description? Is there a link to a project page or paper? Are there credits at the end of the video? What account is publishing the video? Even if you can narrow down the institution or company or lab, you might be able to get a sense of whether they’re working on autonomy or teleoperation.
  • What kind of task is it? You’re most likely to see teleoperation in tasks that would be especially difficult for a robot to do autonomously. At the moment, that’s predominantly manipulation tasks that aren’t well structured—for example, getting multiple objects to interact with each other, handling things that are difficult to model (like fabrics), or extended multistep tasks. If you see a robot doing this stuff quickly and well, it’s worth questioning whether it’s autonomous.
  • Is the robot just too good? I always start asking more questions when a robot demo strikes me as just too impressive. But when does impressive become too impressive? Personally, I think a robot demonstrating human-level performance at just about any complex task is too impressive. Some autonomous robots definitely have reached that benchmark, but not many, and the circumstances of them doing so are usually atypical. Furthermore, it takes a lot of work to reach humanlike performance with an autonomous system, so there’s usually some warning in the form of previous work. If you see an impressive demo that comes out of nowhere, showcasing an autonomous capability without any recent precedents, that’s probably too impressive. Remember that it can be tricky with a video because you have no idea whether you’re watching the first take or the 500th, and that itself is a good thing to be aware of—even if it turns out that a demo is fully autonomous, there are many other ways of obfuscating how successful the system actually is.
  • Is it too fast? Autonomous robots are well known for being very fast and precise, but only in the context of structured tasks. For complex manipulation tasks, robots need to sense their environment, decide what to do next, and then plan how to move. This takes time. If you see an extended task that consists of multiple parts but the system never stops moving, that suggests it’s not fully autonomous.
  • Does it move like a human? Robots like to move optimally. Humans might also like to move optimally, but we’re bad at it. Autonomous robots tend to move smoothly and fluidly, while teleoperated robots often display small movements that don’t make sense in the context of the task, but are very humanlike in nature. For example, finger motions that are unrelated to gripping, or returning an arm to a natural rest position for no particular reason, or being just a little bit sloppy in general. If the motions seem humanlike, that’s usually a sign of a human in the loop rather than a robot that’s just so good at doing a task that it looks human.

None of these points make it impossible for an autonomous robot demo to come out of nowhere and blow everyone away. Improbable, perhaps, but not impossible. And the rare moments when that actually happens is part of what makes robotics so exciting. That’s why it’s so important to understand what’s going on when you see a robot doing something amazing, though—knowing how it’s done, and all of the work that went into it, can only make it more impressive.

This article was inspired by Peter Corke‘s LinkedIn post, What’s with all these deceptive teleoperation demos? And extra thanks to Peter for his feedback on an early draft of this article.



While organic thin-film transistors built on flexible plastic have been around long enough for people to start discussing a Moore’s Law for bendable ICs, memory devices for these flexible electronics have been a bit more elusive. Now researchers from Tsinghua University in China have developed a fully flexible resistive random access memory device, dubbed FlexRAM, that offers another approach: a liquid one.

In research described in the journal Advanced Materials, the researchers have used a gallium-based liquid metal to achieve FlexRAM’s data writing and reading process. In an example of biomimicry, the gallium-based liquid metal (GLM) droplets undergo oxidation and reduction mechanisms while in a solution environment that mimic the hyperpolarization and depolarization of neurons.

“This breakthrough fundamentally changes traditional notions of flexible memory, offering a theoretical foundation and technical path for future soft intelligent robots, brain-machine interface systems, and wearable/implantable electronic devices.”
—Jing Liu, Tsinghua University

These positive and negative bias voltages define the writing of information “1” and “0,” respectively. When a low voltage is applied, the liquid metal is oxidized, corresponding to the high-resistance state of “1.” By reversing the voltage polarity, it returns the metal to its initial low-resistance state of “0.” This reversible switching process allows for the storage and erasure of data.

To showcase the reading and writing capabilities of FlexRAM, the researchers integrated it into a software and hardware setup. Through computer commands, they encoded a string of letters and numbers, represented in the form of 0s and 1s, onto an array of eight FlexRAM storage units, equivalent to one byte of data information. The digital signal from the computer underwent conversion into an analog signal using pulse-width modulation to precisely control the oxidation and reduction of the liquid metal.

Photographs of the oxidation and reduction state of the gallium-based liquid metal at the heart of FlexRAM.Jing Liu/Tsinghua University

The present prototype is a volatile memory, according to Jing Liu, a professor at the Department of Biomedical Engineering at Tsinghua University. But Liu contends that the memory principle allows for the development of the device into different forms of memory.

This contention is supported by the unusual phenomenon that the data stored in FlexRAM persists even when the power is switched off. In a low or no-oxygen environment, FlexRAM can retain its data for up to 43,200 seconds (12 hours). It also exhibits repeatable use, maintaining stable performance for over 3,500 cycles of operation.

“This breakthrough fundamentally changes traditional notions of flexible memory, offering a theoretical foundation and technical path for future soft intelligent robots, brain-machine interface systems, and wearable/implantable electronic devices,” said Liu.

The GLM droplets are encapsulated in Ecoflex, a stretchable biopolymer. Using a 3D printer, the researchers printed Ecoflex molds and injected gallium-based liquid metal droplets and a solution of polyvinyl acetate hydrogel separately into the cavities in the mold. The hydrogel not only prevents solution leakage but also enhances the mechanical properties of the device, increasing its resistance ratio.

“FlexRAM could be incorporated into entire liquid-based computing systems, functioning as a logic device.”
—Jing Liu, Tsinghua University

In the present prototype, an array of 8 FlexRAM units can store one byte of information.

At this conceptual demonstration stage, millimeter-scale resolution molding is sufficient for demonstration of its working principle, Liu notes.

“The conceivable size scale for these FlexRAM devices can range widely,” said Liu. “For example, the size for each of the droplet memory elements can be from millimeter to nano-scale droplets. Interestingly, as revealed by the present study, the smaller the droplet size, the more sensitive the memory response.”

This groundbreaking work paves the way for the realization of brain-like circuits, aligning with concepts proposed by researchers such as Stuart Parkin at IBM over a decade ago. “FlexRAM could be incorporated into entire liquid-based computing systems, functioning as a logic device,” Liu envisions.

As researchers and engineers continue to address challenges and refine the technology, the potential applications of FlexRAM in soft robotics, brain-machine interface systems, and wearable/implantable electronic could be significant.



While organic thin-film transistors built on flexible plastic have been around long enough for people to start discussing a Moore’s Law for bendable ICs, memory devices for these flexible electronics have been a bit more elusive. Now researchers from Tsinghua University in China have developed a fully flexible resistive random access memory device, dubbed FlexRAM, that offers another approach: a liquid one.

In research described in the journal Advanced Materials, the researchers have used a gallium-based liquid metal to achieve FlexRAM’s data writing and reading process. In an example of biomimicry, the gallium-based liquid metal (GLM) droplets undergo oxidation and reduction mechanisms while in a solution environment that mimic the hyperpolarization and depolarization of neurons.

“This breakthrough fundamentally changes traditional notions of flexible memory, offering a theoretical foundation and technical path for future soft intelligent robots, brain-machine interface systems, and wearable/implantable electronic devices.”
—Jing Liu, Tsinghua University

These positive and negative bias voltages define the writing of information “1” and “0,” respectively. When a low voltage is applied, the liquid metal is oxidized, corresponding to the high-resistance state of “1.” By reversing the voltage polarity, it returns the metal to its initial low-resistance state of “0.” This reversible switching process allows for the storage and erasure of data.

To showcase the reading and writing capabilities of FlexRAM, the researchers integrated it into a software and hardware setup. Through computer commands, they encoded a string of letters and numbers, represented in the form of 0s and 1s, onto an array of eight FlexRAM storage units, equivalent to one byte of data information. The digital signal from the computer underwent conversion into an analog signal using pulse-width modulation to precisely control the oxidation and reduction of the liquid metal.

Photographs of the oxidation and reduction state of the gallium-based liquid metal at the heart of FlexRAM.Jing Liu/Tsinghua University

The present prototype is a volatile memory, according to Jing Liu, a professor at the Department of Biomedical Engineering at Tsinghua University. But Liu contends that the memory principle allows for the development of the device into different forms of memory.

This contention is supported by the unusual phenomenon that the data stored in FlexRAM persists even when the power is switched off. In a low or no-oxygen environment, FlexRAM can retain its data for up to 43,200 seconds (12 hours). It also exhibits repeatable use, maintaining stable performance for over 3,500 cycles of operation.

“This breakthrough fundamentally changes traditional notions of flexible memory, offering a theoretical foundation and technical path for future soft intelligent robots, brain-machine interface systems, and wearable/implantable electronic devices,” said Liu.

The GLM droplets are encapsulated in Ecoflex, a stretchable biopolymer. Using a 3D printer, the researchers printed Ecoflex molds and injected gallium-based liquid metal droplets and a solution of polyvinyl acetate hydrogel separately into the cavities in the mold. The hydrogel not only prevents solution leakage but also enhances the mechanical properties of the device, increasing its resistance ratio.

“FlexRAM could be incorporated into entire liquid-based computing systems, functioning as a logic device.”
—Jing Liu, Tsinghua University

In the present prototype, an array of 8 FlexRAM units can store one byte of information.

At this conceptual demonstration stage, millimeter-scale resolution molding is sufficient for demonstration of its working principle, Liu notes.

“The conceivable size scale for these FlexRAM devices can range widely,” said Liu. “For example, the size for each of the droplet memory elements can be from millimeter to nano-scale droplets. Interestingly, as revealed by the present study, the smaller the droplet size, the more sensitive the memory response.”

This groundbreaking work paves the way for the realization of brain-like circuits, aligning with concepts proposed by researchers such as Stuart Parkin at IBM over a decade ago. “FlexRAM could be incorporated into entire liquid-based computing systems, functioning as a logic device,” Liu envisions.

As researchers and engineers continue to address challenges and refine the technology, the potential applications of FlexRAM in soft robotics, brain-machine interface systems, and wearable/implantable electronic could be significant.



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.

Cybathlon Challenges: 2 February 2024, ZURICHEurobot Open 2024: 8–11 May 2024, LA ROCHE-SUR-YON, FRANCEICRA 2024: 13–17 May 2024, YOKOHAMA, JAPANRoboCup 2024: 17–22 July 2024, EINDHOVEN, NETHERLANDS

Enjoy today’s videos!

You may not be familiar with Swiss-Mile, but you’d almost certainly recognize its robot: it’s the ANYmal with wheels on its feet that can do all kinds of amazing things. Swiss-Mile has just announced a seed round to commercialize these capabilities across quadrupedal platforms, including Unitree’s, which means it’s even affordable-ish!

It’s always so cool to see impressive robotics research move toward commercialization, and I’ve already started saving up for one of these of my own.

[ Swiss-Mile ]

Thanks Marko!

This video presents the capabilities of PAL Robotics’ TALOS robot as it demonstrates agile and robust walking using Model Predictive Control (MPC) references sent to a Whole-Body Inverse Dynamics (WBID) controller developed in collaboration with Dynamograde. The footage shows TALOS navigating various challenging terrains, including stairs and slopes, while handling unexpected disturbances and additional weight.

[ PAL Robotics ]

Thanks Lorna!

Do you want to create a spectacular bimanual manipulation demo? All it takes is this teleoperation system and a carefully cropped camera shot! This is based on the Mobile ALOHA system from Stanford that we featured in Video Friday last week.

[ AgileX ]

Wing is still trying to make the drone-delivery thing work, and it’s got a new, bigger drone to deliver even more stuff at once.

[ Wing ]

A lot of robotics research claims to be about search and rescue and disaster relief, but it really looks like RSL’s ANYmal can actually pull it off.

And here’s even more impressive video, along with some detail about how the system works.

[ Paper ]

This might be the most appropriate soundtrack for a robot video that I’ve ever heard.

Snakes have long captivated robotics researchers due to their effective locomotion, flexible body structure, and ability to adapt their skin friction to different terrains. While extensive research has delved into serpentine locomotion, there remains a gap in exploring rectilinear locomotion as a robotic solution for navigating through narrow spaces. In this study, we describe the fundamental principles of rectilinear locomotion and apply them to design a soft crawling robot using origami modules constructed from laminated fabrics.

[ SDU ]

We wrote about Fotokite’s innovative tethered drone seven or eight years ago, and it’s good to see the company is still doing solid work.

I do miss the consumer version, though.

[ Fotokite ]

[ JDP ] via [ Petapixel ]

This is SHIVAA the strawberry picking robot of DFKI Robotics Innovation Center. The system is being developed in the RoLand (Robotic Systems in Agriculture) project, coordinated by the #RoboticsInnovationCenter (RIC) of the DFKI Bremen. Within the project we design and develop a semi-autonomous, mobile system that is capable of harvesting strawberries independent of human interaction.

[ DFKI ]

On December 6, 2023, Demarcus Edwards talked to Robotics students as a speaker in the Undergraduate Robotics Pathways & Careers Speaker Series, which aims to answer the question: “What can I do with a robotics degree?”

[ Michigan Robotics ]

This movie, Loss of Sensation, was released in Russia in 1935. It seems to be the movie that really, really irritated Karel Čapek, because they made his “robots” into mechanical beings instead of biological ones.

[ IMDB ]



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.

Cybathlon Challenges: 2 February 2024, ZURICHEurobot Open 2024: 8–11 May 2024, LA ROCHE-SUR-YON, FRANCEICRA 2024: 13–17 May 2024, YOKOHAMA, JAPANRoboCup 2024: 17–22 July 2024, EINDHOVEN, NETHERLANDS

Enjoy today’s videos!

You may not be familiar with Swiss-Mile, but you’d almost certainly recognize its robot: it’s the ANYmal with wheels on its feet that can do all kinds of amazing things. Swiss-Mile has just announced a seed round to commercialize these capabilities across quadrupedal platforms, including Unitree’s, which means it’s even affordable-ish!

It’s always so cool to see impressive robotics research move toward commercialization, and I’ve already started saving up for one of these of my own.

[ Swiss-Mile ]

Thanks Marko!

This video presents the capabilities of PAL Robotics’ TALOS robot as it demonstrates agile and robust walking using Model Predictive Control (MPC) references sent to a Whole-Body Inverse Dynamics (WBID) controller developed in collaboration with Dynamograde. The footage shows TALOS navigating various challenging terrains, including stairs and slopes, while handling unexpected disturbances and additional weight.

[ PAL Robotics ]

Thanks Lorna!

Do you want to create a spectacular bimanual manipulation demo? All it takes is this teleoperation system and a carefully cropped camera shot! This is based on the Mobile ALOHA system from Stanford that we featured in Video Friday last week.

[ AgileX ]

Wing is still trying to make the drone-delivery thing work, and it’s got a new, bigger drone to deliver even more stuff at once.

[ Wing ]

A lot of robotics research claims to be about search and rescue and disaster relief, but it really looks like RSL’s ANYmal can actually pull it off.

And here’s even more impressive video, along with some detail about how the system works.

[ Paper ]

This might be the most appropriate soundtrack for a robot video that I’ve ever heard.

Snakes have long captivated robotics researchers due to their effective locomotion, flexible body structure, and ability to adapt their skin friction to different terrains. While extensive research has delved into serpentine locomotion, there remains a gap in exploring rectilinear locomotion as a robotic solution for navigating through narrow spaces. In this study, we describe the fundamental principles of rectilinear locomotion and apply them to design a soft crawling robot using origami modules constructed from laminated fabrics.

[ SDU ]

We wrote about Fotokite’s innovative tethered drone seven or eight years ago, and it’s good to see the company is still doing solid work.

I do miss the consumer version, though.

[ Fotokite ]

[ JDP ] via [ Petapixel ]

This is SHIVAA the strawberry picking robot of DFKI Robotics Innovation Center. The system is being developed in the RoLand (Robotic Systems in Agriculture) project, coordinated by the #RoboticsInnovationCenter (RIC) of the DFKI Bremen. Within the project we design and develop a semi-autonomous, mobile system that is capable of harvesting strawberries independent of human interaction.

[ DFKI ]

On December 6, 2023, Demarcus Edwards talked to Robotics students as a speaker in the Undergraduate Robotics Pathways & Careers Speaker Series, which aims to answer the question: “What can I do with a robotics degree?”

[ Michigan Robotics ]

This movie, Loss of Sensation, was released in Russia in 1935. It seems to be the movie that really, really irritated Karel Čapek, because they made his “robots” into mechanical beings instead of biological ones.

[ IMDB ]

Experiments on physical continuum robot are the gold standard for evaluations. Currently, as no commercial continuum robot platform is available, a large variety of early-stage prototypes exists. These prototypes are developed by individual research groups and are often used for a single publication. Thus, a significant amount of time is devoted to creating proprietary hardware and software hindering the development of a common platform, and shifting away scarce time and efforts from the main research challenges. We address this problem by proposing an open-source actuation module, which can be used to build different types of continuum robots. It consists of a high-torque brushless electric motor, a high resolution optical encoder, and a low-gear-ratio transmission. For this article, we create three different types of continuum robots. In addition, we illustrate, for the first time, that continuum robots built with our actuation module can proprioceptively detect external forces. Consequently, our approach opens untapped and under-investigated research directions related to the dynamics and advanced control of continuum robots, where sensing the generalized flow and effort is mandatory. Besides that, we democratize continuum robots research by providing open-source software and hardware with our initiative called the Open Continuum Robotics Project, to increase the accessibility and reproducibility of advanced methods.

Agriculture 4.0 presents several challenges for the automation of various operations, including the fundamental task of harvesting. One of the crucial aspects in the automatic harvesting of high value crops is the grip and detachment of delicate fruits without spoiling them or interfering with the environment. Soft robotic systems, particularly soft grippers, offer a promising solution for this problem, as they can operate in unstructured environments, manipulate objects delicately, and interact safely with humans. In this context, this article presents a soft gripper design for harvesting as well as for pick-and-place operations of small and medium-sized fruits. The gripper is fabricated using the 3D printing technology with a flexible thermoplastic elastomer filament. This approach enables the production of an economical, compact, easily replicable, and interchangeable gripper by utilizing soft robotics principles, such as flexible structures and pneumatic actuation.

Soft robots are characterized by their mechanical compliance, making them well-suited for various bio-inspired applications. However, the challenge of preserving their flexibility during deployment has necessitated using soft sensors which can enhance their mobility, energy efficiency, and spatial adaptability. Through emulating the structure, strategies, and working principles of human senses, soft robots can detect stimuli without direct contact with soft touchless sensors and tactile stimuli. This has resulted in noteworthy progress within the field of soft robotics. Nevertheless, soft, touchless sensors offer the advantage of non-invasive sensing and gripping without the drawbacks linked to physical contact. Consequently, the popularity of soft touchless sensors has grown in recent years, as they facilitate intuitive and safe interactions with humans, other robots, and the surrounding environment. This review explores the emerging confluence of touchless sensing and soft robotics, outlining a roadmap for deployable soft robots to achieve human-level dexterity.



You’re familiar with Karel Čapek, right? If not, you should be—he’s the guy who (along with his brother Josef) invented the word “robot.” Čapek introduced robots to the world in 1921, when his play “R.U.R.” (subtitled “Rossum’s Universal Robots”) was first performed in Prague. It was performed in New York City the next year, and by the year after that, it had been translated into 30 languages. Translated, that is, except for the word “robot” itself, which originally described artificial humans but within a decade of its introduction came to mean things that were mechanical and electronic in nature.

Čapek, it turns out, was a little miffed that his “robots” had been so hijacked, and in 1935, he wrote a column in the Lidové noviny “defending” his vision of what robots should be, while also resigning himself to what they had become. A new translation of this column is included as an afterword in a new English translation of R.U.R. that is accompanied by 20 essays exploring robotics, philosophy, politics, and AI in the context of the play, and it makes for fascinating reading.

R.U.R. and the Vision of Artificial Life is edited by Jitka Čejková, a professor at the Chemical Robotics Laboratory at the University of Chemistry and Technology Prague, and whose research interests arguably make her one of the most qualified people to write about Čapek’s perspective on robots. “The chemical robots in the form of microparticles that we designed and investigated, and that had properties similar to living cells, were much closer to Čapek’s original ideas than any other robots today,” Čejková explains in the book’s introduction. These microparticles can exhibit surprisingly complex autonomous behaviors under specific situations, like solving simple mazes:

“I started to call these droplets liquid robots,” says Čejková. “Just as Rossum’s robots were artificial human beings that only looked like humans and could imitate only certain characteristics and behaviors of humans, so liquid robots, as artificial cells, only partially imitate the behavior of their living counterparts.”

What is or is not called a robot is an ongoing debate that most roboticists seem to try to avoid, but personally, I appreciate the idea that very broadly, a robot is something that seems alive but isn’t—something with independent embodied intelligence. Perhaps the requirement that a robot is mechanical and electronic is too strict, although as Čapek himself realized a hundred years ago, what defines a robot has escaped from the control of anyone, even its creator. Here then is his column from 1935, excerpted from R.U.R. and the Vision of Artificial Life, released just today:

“THE AUTHOR OF THE ROBOTS DEFENDS HIMSELF” By Karel ČapekPublished in Lidové noviny, June 9, 1935

I know it is a sign of ingratitude on the part of the author, if he raises both hands against a certain popularity that has befallen something which is called his spiritual brainchild; for that matter, he is aware that by doing so he can no longer change a thing. The author was silent a goodly time and kept his own counsel, while the notion that robots have limbs of metal and innards of wire and cogwheels (or the like) has become current; he has learned, without any great pleasure, that genuine steel robots have started to appear, robots that move in various directions, tell the time, and even fly airplanes; but when he recently read that, in Moscow, they have shot a major film, in which the world is trampled underfoot by mechanical robots, driven by electromagnetic waves, he developed a strong urge to protest, at least in the name of his own robots. For his robots were not mechanisms. They were not made of sheet metal and cogwheels. They were not a celebration of mechanical engineering. If the author was thinking of any of the marvels of the human spirit during their creation, it was not of technology, but of science. With outright horror, he refuses any responsibility for the thought that machines could take the place of people, or that anything like life, love, or rebellion could ever awaken in their cogwheels. He would regard this somber vision as an unforgivable overvaluation of mechanics or as a severe insult to life.

The author of the robots appeals to the fact that he must know the most about it: and therefore he pronounces that his robots were created quite differently—that is, by a chemical path. The author was thinking about modern chemistry, which in various emulsions (or whatever they are called) has located substances and forms that in some ways behave like living matter. He was thinking about biological chemistry, which is constantly discovering new chemical agents that have a direct regulatory influence on living matter; about chemistry, which is finding—and to some extent already building—those various enzymes, hormones, and vitamins that give living matter its ability to grow and multiply and arrange all the other necessities of life. Perhaps, as a scientific layman, he might develop an urge to attribute this patient ingenious scholarly tinkering with the ability to one day produce, by artificial means, a living cell in the test tube; but for many reasons, amongst which also belonged a respect for life, he could not resolve to deal so frivolously with this mystery. That is why he created a new kind of matter by chemical synthesis, one which simply behaves a lot like the living; it is an organic substance, different from that from which living cells are made; it is something like another alternative to life, a material substrate in which life could have evolved if it had not, from the beginning, taken a different path. We do not have to suppose that all the different possibilities of creation have been exhausted on our planet. The author of the robots would regard it as an act of scientific bad taste if he had brought something to life with brass cogwheels or created life in the test tube; the way he imagined it, he created only a new foundation for life, which began to behave like living matter, and which could therefore have become a vehicle of life—but a life which remains an unimaginable and incomprehensible mystery. This life will reach its fulfillment only when (with the aid of considerable inaccuracy and mysticism) the robots acquire souls. From which it is evident that the author did not invent his robots with the technological hubris of a mechanical engineer, but with the metaphysical humility of a spiritualist.

Well then, the author cannot be blamed for what might be called the worldwide humbug over the robots. The author did not intend to furnish the world with plate metal dummies stuffed with cogwheels, photocells, and other mechanical gizmos. It appears, however, that the modern world is not interested in his scientific robots and has replaced them with technological ones; and these are, as is apparent, the true flesh-of-our-flesh of our age. The world needed mechanical robots, for it believes in machines more than it believes in life; it is fascinated more by the marvels of technology than by the miracle of life. For which reason, the author who wanted—through his insurgent robots, striving for a soul—to protest against the mechanical superstition of our times, must in the end claim something which nobody can deny him: the honor that he was defeated.

Excerpted from R.U.R. and the Vision of Artificial Life, by Karel Čapek, edited by Jitka Čejková. Published by The MIT Press. Copyright © 2024 MIT. All rights reserved.



You’re familiar with Karel Čapek, right? If not, you should be—he’s the guy who (along with his brother Josef) invented the word “robot.” Čapek introduced robots to the world in 1921, when his play “R.U.R.” (subtitled “Rossum’s Universal Robots”) was first performed in Prague. It was performed in New York City the next year, and by the year after that, it had been translated into 30 languages. Translated, that is, except for the word “robot” itself, which originally described artificial humans but within a decade of its introduction came to mean things that were mechanical and electronic in nature.

Čapek, it turns out, was a little miffed that his “robots” had been so hijacked, and in 1935, he wrote a column in the Lidové noviny “defending” his vision of what robots should be, while also resigning himself to what they had become. A new translation of this column is included as an afterword in a new English translation of R.U.R. that is accompanied by 20 essays exploring robotics, philosophy, politics, and AI in the context of the play, and it makes for fascinating reading.

R.U.R. and the Vision of Artificial Life is edited by Jitka Čejková, a professor at the Chemical Robotics Laboratory at the University of Chemistry and Technology Prague, and whose research interests arguably make her one of the most qualified people to write about Čapek’s perspective on robots. “The chemical robots in the form of microparticles that we designed and investigated, and that had properties similar to living cells, were much closer to Čapek’s original ideas than any other robots today,” Čejková explains in the book’s introduction. These microparticles can exhibit surprisingly complex autonomous behaviors under specific situations, like solving simple mazes:

“I started to call these droplets liquid robots,” says Čejková. “Just as Rossum’s robots were artificial human beings that only looked like humans and could imitate only certain characteristics and behaviors of humans, so liquid robots, as artificial cells, only partially imitate the behavior of their living counterparts.”

What is or is not called a robot is an ongoing debate that most roboticists seem to try to avoid, but personally, I appreciate the idea that very broadly, a robot is something that seems alive but isn’t—something with independent embodied intelligence. Perhaps the requirement that a robot is mechanical and electronic is too strict, although as Čapek himself realized a hundred years ago, what defines a robot has escaped from the control of anyone, even its creator. Here then is his column from 1935, excerpted from R.U.R. and the Vision of Artificial Life, released just today:

“THE AUTHOR OF THE ROBOTS DEFENDS HIMSELF” By Karel ČapekPublished in Lidové noviny, June 9, 1935

I know it is a sign of ingratitude on the part of the author, if he raises both hands against a certain popularity that has befallen something which is called his spiritual brainchild; for that matter, he is aware that by doing so he can no longer change a thing. The author was silent a goodly time and kept his own counsel, while the notion that robots have limbs of metal and innards of wire and cogwheels (or the like) has become current; he has learned, without any great pleasure, that genuine steel robots have started to appear, robots that move in various directions, tell the time, and even fly airplanes; but when he recently read that, in Moscow, they have shot a major film, in which the world is trampled underfoot by mechanical robots, driven by electromagnetic waves, he developed a strong urge to protest, at least in the name of his own robots. For his robots were not mechanisms. They were not made of sheet metal and cogwheels. They were not a celebration of mechanical engineering. If the author was thinking of any of the marvels of the human spirit during their creation, it was not of technology, but of science. With outright horror, he refuses any responsibility for the thought that machines could take the place of people, or that anything like life, love, or rebellion could ever awaken in their cogwheels. He would regard this somber vision as an unforgivable overvaluation of mechanics or as a severe insult to life.

The author of the robots appeals to the fact that he must know the most about it: and therefore he pronounces that his robots were created quite differently—that is, by a chemical path. The author was thinking about modern chemistry, which in various emulsions (or whatever they are called) has located substances and forms that in some ways behave like living matter. He was thinking about biological chemistry, which is constantly discovering new chemical agents that have a direct regulatory influence on living matter; about chemistry, which is finding—and to some extent already building—those various enzymes, hormones, and vitamins that give living matter its ability to grow and multiply and arrange all the other necessities of life. Perhaps, as a scientific layman, he might develop an urge to attribute this patient ingenious scholarly tinkering with the ability to one day produce, by artificial means, a living cell in the test tube; but for many reasons, amongst which also belonged a respect for life, he could not resolve to deal so frivolously with this mystery. That is why he created a new kind of matter by chemical synthesis, one which simply behaves a lot like the living; it is an organic substance, different from that from which living cells are made; it is something like another alternative to life, a material substrate in which life could have evolved if it had not, from the beginning, taken a different path. We do not have to suppose that all the different possibilities of creation have been exhausted on our planet. The author of the robots would regard it as an act of scientific bad taste if he had brought something to life with brass cogwheels or created life in the test tube; the way he imagined it, he created only a new foundation for life, which began to behave like living matter, and which could therefore have become a vehicle of life—but a life which remains an unimaginable and incomprehensible mystery. This life will reach its fulfillment only when (with the aid of considerable inaccuracy and mysticism) the robots acquire souls. From which it is evident that the author did not invent his robots with the technological hubris of a mechanical engineer, but with the metaphysical humility of a spiritualist.

Well then, the author cannot be blamed for what might be called the worldwide humbug over the robots. The author did not intend to furnish the world with plate metal dummies stuffed with cogwheels, photocells, and other mechanical gizmos. It appears, however, that the modern world is not interested in his scientific robots and has replaced them with technological ones; and these are, as is apparent, the true flesh-of-our-flesh of our age. The world needed mechanical robots, for it believes in machines more than it believes in life; it is fascinated more by the marvels of technology than by the miracle of life. For which reason, the author who wanted—through his insurgent robots, striving for a soul—to protest against the mechanical superstition of our times, must in the end claim something which nobody can deny him: the honor that he was defeated.

Excerpted from R.U.R. and the Vision of Artificial Life, by Karel Čapek, edited by Jitka Čejková. Published by The MIT Press. Copyright © 2024 MIT. All rights reserved.

This paper presents and discusses the development and deployment of a tour guide robot as part of the 5 g-TOURS EU research project, aimed at developing applications enabled by 5G technology in different use cases. The objective is the development of an autonomous robotic application where intelligence is off-loaded to a remote machine via 5G network, so as to lift most of the computational load from the robot itself. The application uses components that have been widely studied in robotics, (i.e., localization, mapping, planning, interaction). However, the characteristics of the network and interactions with visitors in the wild introduce specific problems which must be taken into account. The paper discusses in detail such problems, summarizing the main results achieved both from the methodological and the experimental standpoint, and is completed by the description of the general functional architecture of the whole system, including navigation and operational services. The software implementation is also publicly available.



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.

Cybathlon Challenges: 2 February 2024, ZURICHEurobot Open 2024: 8–11 May 2024, LA ROCHE-SUR-YON, FRANCEICRA 2024: 13–17 May 2024, YOKOHAMA, JAPANRoboCup 2024: 17–22 July 2024, EINDHOVEN, NETHERLANDS

Enjoy today’s videos!

Figure’s robot is watching videos of humans making coffee, and then making coffee on its own.

While this is certainly impressive, just be aware that it’s not at all clear from the video exactly how impressive it is.

[ Figure ]

It’s really the shoes that get me with Westwood’s THEMIS robot.

THEMIS can also deliver a package just as well as a human can, if not better!

And I appreciate the inclusion of all of these outtakes, too:

[ Westwood Robotics ]

Kepler Exploration Robot recently unveiled its latest innovation, the Kepler Forerunner series of general-purpose humanoid robots. This advanced humanoid stands at a height of 178cm (5’10”), weighs 85kg (187 lbs.), and boasts an intelligent and dexterous hand with 12 degrees of freedom. The entire body has up to 40 degrees of freedom, enabling functionalities such as navigating complex terrains, intelligent obstacle avoidance, flexible manipulation of hands, powerful lifting and carrying of heavy loads, hand-eye coordination, and intelligent interactive communication.

[ Kepler Exploration ]

Introducing the new Ballie, your true AI companion. With more advanced intelligence, Ballie can come right to you and project visuals on your walls. It can also help you interact with other connected devices or take care of hassles.

[ Samsung ]

There is a thing called Drone Soccer that got some exposure at CES this week, but apparently it’s been around for several years, and originated in South Korea. Inspired by Quiddich, targeted at STEM students.

[ Drone Soccer ]

Every so often, JPL dumps a bunch of raw footage onto YouTube. This time, there’s Perseverance’s view of Ingenuity taking off, a test of the EELS robot, and an unusual sample tube drop test.

[ JPL ]

Our first months delivering to Walmart customers have made one thing clear: Demand for drone delivery is real. On the heels of our Dallas-wide FAA approvals, today we announced that millions of new DFW-area customers will have access to drone delivery in 2024!

[ Wing ]

Dave Burke works with Biomechatronics researcher Michael Fernandez to test a prosthesis with neural control, by cutting a sheet of paper with scissors. This is the first time in 30 years that Dave has performed this task with his missing hand.

[ MIT ]

Meet DJI’s first delivery drone—FlyCart 30. Overcome traditional transport challenges and start a new era of dynamic aerial delivery with large payload capacity, long operation range, high reliability, and intelligent features.

[ DJI ]

The Waymo Driver autonomously operating both a passenger vehicle and class 8 truck safely in various freeway scenarios, including on-ramps and off-ramps, lane merges, and sharing the road with others.

[ Waymo ]

In this paper, we present DiffuseBot, a physics-augmented diffusion model that generates soft robot morphologies capable of excelling in a wide spectrum of tasks. DiffuseBot bridges the gap between virtually generated content and physical utility by (i) augmenting the diffusion process with a physical dynamical simulation which provides a certificate of performance, and ii) introducing a co-design procedure that jointly optimizes physical design and control by leveraging information about physical sensitivities from differentiable simulation.

[ Paper ]



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.

Cybathlon Challenges: 2 February 2024, ZURICHEurobot Open 2024: 8–11 May 2024, LA ROCHE-SUR-YON, FRANCEICRA 2024: 13–17 May 2024, YOKOHAMA, JAPANRoboCup 2024: 17–22 July 2024, EINDHOVEN, NETHERLANDS

Enjoy today’s videos!

Figure’s robot is watching videos of humans making coffee, and then making coffee on its own.

While this is certainly impressive, just be aware that it’s not at all clear from the video exactly how impressive it is.

[ Figure ]

It’s really the shoes that get me with Westwood’s THEMIS robot.

THEMIS can also deliver a package just as well as a human can, if not better!

And I appreciate the inclusion of all of these outtakes, too:

[ Westwood Robotics ]

Kepler Exploration Robot recently unveiled its latest innovation, the Kepler Forerunner series of general-purpose humanoid robots. This advanced humanoid stands at a height of 178cm (5’10”), weighs 85kg (187 lbs.), and boasts an intelligent and dexterous hand with 12 degrees of freedom. The entire body has up to 40 degrees of freedom, enabling functionalities such as navigating complex terrains, intelligent obstacle avoidance, flexible manipulation of hands, powerful lifting and carrying of heavy loads, hand-eye coordination, and intelligent interactive communication.

[ Kepler Exploration ]

Introducing the new Ballie, your true AI companion. With more advanced intelligence, Ballie can come right to you and project visuals on your walls. It can also help you interact with other connected devices or take care of hassles.

[ Samsung ]

There is a thing called Drone Soccer that got some exposure at CES this week, but apparently it’s been around for several years, and originated in South Korea. Inspired by Quiddich, targeted at STEM students.

[ Drone Soccer ]

Every so often, JPL dumps a bunch of raw footage onto YouTube. This time, there’s Perseverance’s view of Ingenuity taking off, a test of the EELS robot, and an unusual sample tube drop test.

[ JPL ]

Our first months delivering to Walmart customers have made one thing clear: Demand for drone delivery is real. On the heels of our Dallas-wide FAA approvals, today we announced that millions of new DFW-area customers will have access to drone delivery in 2024!

[ Wing ]

Dave Burke works with Biomechatronics researcher Michael Fernandez to test a prosthesis with neural control, by cutting a sheet of paper with scissors. This is the first time in 30 years that Dave has performed this task with his missing hand.

[ MIT ]

Meet DJI’s first delivery drone—FlyCart 30. Overcome traditional transport challenges and start a new era of dynamic aerial delivery with large payload capacity, long operation range, high reliability, and intelligent features.

[ DJI ]

The Waymo Driver autonomously operating both a passenger vehicle and class 8 truck safely in various freeway scenarios, including on-ramps and off-ramps, lane merges, and sharing the road with others.

[ Waymo ]

In this paper, we present DiffuseBot, a physics-augmented diffusion model that generates soft robot morphologies capable of excelling in a wide spectrum of tasks. DiffuseBot bridges the gap between virtually generated content and physical utility by (i) augmenting the diffusion process with a physical dynamical simulation which provides a certificate of performance, and ii) introducing a co-design procedure that jointly optimizes physical design and control by leveraging information about physical sensitivities from differentiable simulation.

[ Paper ]

Introduction: The modern worldwide trend toward sedentary behavior comes with significant health risks. An accompanying wave of health technologies has tried to encourage physical activity, but these approaches often yield limited use and retention. Due to their unique ability to serve as both a health-promoting technology and a social peer, we propose robots as a game-changing solution for encouraging physical activity.

Methods: This article analyzes the eight exergames we previously created for the Rethink Baxter Research Robot in terms of four key components that are grounded in the video-game literature: repetition, pattern matching, music, and social design. We use these four game facets to assess gameplay data from 40 adult users who each experienced the games in balanced random order.

Results: In agreement with prior research, our results show that relevant musical cultural references, recognizable social analogues, and gameplay clarity are good strategies for taking an otherwise highly repetitive physical activity and making it engaging and popular among users.

Discussion: Others who study socially assistive robots and rehabilitation robotics can benefit from this work by considering the presented design attributes to generate future hypotheses and by using our eight open-source games to pursue follow-up work on social-physical exercise with robots.

Human-robot cooperation (HRC) is becoming increasingly relevant with the surge in collaborative robots (cobots) for industrial applications. Examples of humans and robots cooperating actively on the same workpiece can be found in research labs around the world, but industrial applications are still mostly limited to robots and humans taking turns. In this paper, we use a cooperative lifting task (co-lift) as a case study to explore how well this task can be learned within a limited time, and how background factors of users may impact learning. The experimental study included 32 healthy adults from 20 to 54 years who performed a co-lift with a collaborative robot. The physical setup is designed as a gamified user training system as research has validated that gamification is an effective methodology for user training. Human motions and gestures were measured using Inertial Measurement Unit (IMU) sensors and used to interact with the robot across three role distributions: human as the leader, robot as the leader, and shared leadership. We find that regardless of age, gender, job category, gaming background, and familiarity with robots, the learning curve of all users showed a satisfactory progression and that all users could achieve successful cooperation with the robot on the co-lift task after seven or fewer trials. The data indicates that some of the background factors of the users such as occupation, past gaming habits, etc., may affect learning outcomes, which will be explored further in future experiments. Overall, the results indicate that the potential of the adoption of HRC in the industry is promising for a diverse set of users after a relatively short training process.

Inflatable fabric beams (IFBs) integrating pleat folds can generate complex motion by modifying the pleat characteristics (e.g., dimensions, orientations). However, the capability of the IFB to return to the folded configuration relies upon the elasticity of the fabrics, requiring additional pressure inputs or complementary mechanisms. Using soft compliant elements (SCEs) assembled onto pleat folds is an appealing approach to improving the IFB elasticity and providing a range of spatial configurations when pressurized. This study introduces an actuator comprising an IFB with pleat folds and SCEs. By methodologically assembling the SCEs onto the pleat folds, we constrain the IFB unfolding to achieve out-of-plane motion at 5 kPa. Besides, the proposed actuator can generate angular displacement by regulating the input pressure (> 5 kPa). A matrix-based representation and model are proposed to analyze the actuator motion. We experimentally study the actuator’s angular displacement by modifying SCE shapes, fold dimensions, and assembly distances of SCEs. Moreover, we analyze the effects of incorporating two SCEs onto a pleat fold. Our results show that the actuator motion can be tuned by integrating SCEs with different stiffness and varying the pleat fold dimensions. In addition, we demonstrate that the integration of two SCEs onto the pleat fold permits the actuator to return to its folded configuration when depressurized. In order to demonstrate the versatility of the proposed actuator, we devise and conduct experiments showcasing the implementation of a planar serial manipulator and a soft gripper with two grasping modalities.

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