Enlarge/ A woman wearing a sweatshirt for the QAnon conspiracy theory on October 11, 2020 in Ronkonkoma, New York. (credit: Stephanie Keith | Getty Images)
Belief in conspiracy theories is rampant, particularly in the US, where some estimates suggest as much as 50 percent of the population believes in at least one outlandish claim. And those beliefs are notoriously difficult to debunk. Challenge a committed conspiracy theorist with facts and evidence, and they'll usually just double down—a phenomenon psychologists usually attribute to motivated reasoning, i.e., a biased way of processing information.
A new paper published in the journal Science is challenging that conventional wisdom, however. Experiments in which an AI chatbot engaged in conversations with people who believed at least one conspiracy theory showed that the interaction significantly reduced the strength of those beliefs, even two months later. The secret to its success: the chatbot, with its access to vast amounts of information across an enormous range of topics, could precisely tailor its counterarguments to each individual.
"These are some of the most fascinating results I've ever seen," co-author Gordon Pennycook, a psychologist at Cornell University, said during a media briefing. "The work overturns a lot of how we thought about conspiracies, that they're the result of various psychological motives and needs. [Participants] were remarkably responsive to evidence. There's been a lot of ink spilled about being in a post-truth world. It's really validating to know that evidence does matter. We can act in a more adaptive way using this new technology to get good evidence in front of people that is specifically relevant to what they think, so it's a much more powerful approach."
A new study examined how humans perceive different types of deception by robots, revealing that people accept some lies more than others. Researchers presented nearly 500 participants with scenarios where robots engaged in external, hidden, and superficial deceptions in medical, cleaning, and retail settings. Participants disapproved most of hidden deceptions, such as a cleaning robot secretly filming, while external lies, like sparing a patient from emotional pain, were viewed more favorably.
Boardwalk Robotics is announcing its entry into the increasingly crowded commercial humanoid(ish) space with Alex, a “workforce transformation” humanoid upper torso designed to work in manufacturing, logistics, and maintenance.
Before we get into Alex, let me take just a minute here to straighten out how Boardwalk Robotics is related to IHMC, the Institute for Human Machine Cognition in Pensacola, Fla. IHMC is, I think it’s fair to say, somewhat legendary when it comes to bipedal robotics—its DARPA Robotics Challenge team took second place in the final event (using a Boston Dynamics DRC Atlas), and when NASA needed someone to teach the agency’s Valkyrie humanoid to walk better, they sent it to IHMC.
Boardwalk, which was founded in 2017, has been a commercial partner with IHMC when it comes to the actual building of robots. The most visible example of this to date has been IHMC’s Nadia humanoid, a research platform which Boardwalk collaborated on and built.There’s obviously a lot of crossover between IHMC and Boardwalk in terms of institutional knowledge and experience, but Alex is a commercial robot developed entirely in-house by Boardwalk.
“We’ve used Nadia to learn a lot in the realm of dynamic locomotion research, and we’re taking all that and sticking it into a manipulation platform that’s ready for commercial work,” says Brandon Shrewsbury, Boardwalk Robotics’ CTO. “With Alex, we’re focusing on the manipulation side first, getting that well established. And then picking the mobility to match the task.”
The first thing you’ll notice about Alex is that it doesn’t have legs, at least for now. Boardwalk’s theory is that for a humanoid to be practical and cost effective in the near term, legs aren’t necessary, and that there are many tasks that offer a good return on investment where a stationary pedestal or a glorified autonomous mobile robotic base would be totally fine.
“There are going to be some problem sets that require legs, but there are many problem sets that don’t,” says Robert Griffin, a technical advisor at Boardwalk. “And there aren’t very many problem sets that don’t require halfway decent manipulation capabilities. So if we can design the manipulation well from the beginning, then we won’t have to depend on legs for making a robot that’s functionally useful.”
It certainly helps that Boardwalk isn’t at all worried about developing legs: “Every time we bring up a new humanoid, it’s something like twice as fast as the previous time,” Griffin says. This will be the eighth humanoid that IHMC has been involved in bringing up—I’d tell you more about all eight of those humanoids, but some of them are so secret that even I don’t know anything about them.Legs are definitely on the road map, but they’re not done yet, and IHMC will have a hand in their development to speed things along: It turns out that already having access to a functional (top of the line, really) locomotion stack is a big head start.
Alex’s actuators are all designed in-house, and the next version will feature new grippers that allow for quicker tool changes.Boardwalk Robotics
While the humanoid space is wide open right now and competition isn’t really an issue, looking ahead, Boardwalk sees safety as one of its primary differentiators since it’s not starting out with legs, says Shrewsbury. “For a full humanoid, there’s no way to make that completely safe. If it falls, it’s going to face-plant.” By keeping Alex on a stable base, it can work closer to humans and potentially move its arms much faster while also preserving a dynamic safety zone.
Alex is available for researchers to purchase immediately.Boardwalk Robotics
Despite its upbringing in research, Alex is not intended to be a research robot. You can buy it for research purposes, if you want, but Boardwalk will be selling Alex as a commercial robot. At the moment, Boardwalk is conducting pilot programs with Alexwhere they’re working in partnership with select customers, with the eventual goal of transitioning to a service model. The first few sectors that Boardwalk is targeting include logistics (because, of course) and food processing, although as Boardwalk CEO Michael Morin tells us, one of the very first pilots is (appropriately enough) in aviation.
Morin, who helped to commercialize Barrett Technologies’ WAM Arm before spending some time at Vicarious Surgical as that company went public, joined Boardwalk to help them turn good engineering into a good product, which is arguably the hardest part of making useful robots (besides all the other hardest parts). “A lot of these companies are just learning about humanoids for the first time,” says Morin. “That makes the customer journey longer. But we’re putting in the effort to educate them on how this could be implemented in their world.”
If you want an Alex of your very own, Boardwalk is currently selecting commercial partners for a few more pilots. And for researchers, the robot is available right now.
Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.
ICRA@40: 23–26 September 2024, ROTTERDAM, NETHERLANDS
At ICRA 2024, in Tokyo last May, we sat down with the director of Shadow Robot, Rich Walker, to talk about the journey toward developing its newest model. Designed for reinforcement learning, the hand is extremely rugged, has three fingers that act like thumbs, and has fingertips that are highly sensitive to touch.
Food Angel is a food delivery robot to help with the problems of food insecurity and homelessness. Utilizing autonomous wheeled robots for this application may seem to be a good approach, especially with a number of successful commercial robotic delivery services. However, besides technical considerations such as range, payload, operation time, autonomy, etc., there are a number of important aspects that still need to be investigated, such as how the general public and the receiving end may feel about using robots for such applications, or human-robot interaction issues such as how to communicate the intent of the robot to the homeless.
The UKRI FLF team RoboHike of UCL Computer Science of the Robot Perception and Learning lab with Forestry England demonstrate the ANYmal robot to help preserve the cultural heritage of an historic mine in the Forest of Dean, Gloucestershire, UK.
This clip is from a reboot of the British TV show “Time Team.” If you’re not already a fan of “Time Team,” let me just say that it is one of the greatest retro reality TV shows ever made, where actual archaeologists wander around the United Kingdom and dig stuff up. If they can find anything. Which they often can’t. And also it has Tony Robinson (from “Blackadder”), who runs everywhere for some reason. Go to Time Team Classics on YouTube for 70+ archived episodes.
UBTECH humanoid robot Walker S Lite is working in Zeekr’s intelligent factory to complete handling tasks at the loading workstation for 21 consecutive days, and assist its employees with logistics work.
Current visual navigation systems often treat the environment as static, lacking the ability to adaptively interact with obstacles. This limitation leads to navigation failure when encountering unavoidable obstructions. In response, we introduce IN-Sight, a novel approach to self-supervised path planning, enabling more effective navigation strategies through interaction with obstacles.
MIT MechE researchers introduce an approach called SimPLE (Simulation to Pick Localize and placE), a method of precise kitting, or pick and place, in which a robot learns to pick, regrasp, and place objects using the object’s computer-aided design (CAD) model, and all without any prior experience or encounters with the specific objects.
Staff, students (and quadruped robots!) from UCL Computer Science wish the Great Britain athletes the best of luck this summer in the Olympic Games & Paralympics.
Walking in tall grass can be hard for robots, because they can’t see the ground that they’re actually stepping on. Here’s a technique to solve that, published in Robotics and Automation Letters last year.
There is no such thing as excess batter on a corn dog, and there is also no such thing as a defective donut. And apparently, making Kool-Aid drink pouches is harder than it looks.
Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.
ICRA@40: 23–26 September 2024, ROTTERDAM, NETHERLANDS
IROS 2024: 14–18 October 2024, ABU DHABI, UNITED ARAB EMIRATES
We introduce Berkeley Humanoid, a reliable and low-cost mid-scale humanoid research platform for learning-based control. Our lightweight, in-house-built robot is designed specifically for learning algorithms with low simulation complexity, anthropomorphic motion, and high reliability against falls. Capable of omnidirectional locomotion and withstanding large perturbations with a compact setup, our system aims for scalable, sim-to-real deployment of learning-based humanoid systems.
This article presents Ray, a new type of audio-animatronic robot head. All the mechanical structure of the robot is built in one step by 3-D printing... This simple, lightweight structure and the separate tendon-based actuation system underneath allow for smooth, fast motions of the robot. We also develop an audio-driven motion generation module that automatically synthesizes natural and rhythmic motions of the head and mouth based on the given audio.
CSAIL researchers introduce a novel approach allowing robots to be trained in simulations of scanned home environments, paving the way for customized household automation accessible to anyone.
NVIDIA CEO Jensen Huang presented a major breakthrough on Project GR00T with WIRED’s Lauren Goode at SIGGRAPH 2024. In a two-minute demonstration video, NVIDIA explained a systematic approach they discovered to scale up robot data, addressing one of the most challenging issues in robotics.
In this research, we investigated the innovative use of a manipulator as a tail in quadruped robots to augment their physical capabilities. Previous studies have primarily focused on enhancing various abilities by attaching robotic tails that function solely as tails on quadruped robots. While these tails improve the performance of the robots, they come with several disadvantages, such as increased overall weight and higher costs. To mitigate these limitations, we propose the use of a 6-DoF manipulator as a tail, allowing it to serve both as a tail and as a manipulator.
In this end-to-end demo, we showcase how MenteeBot transforms the shopping experience for individuals, particularly those using wheelchairs. Through discussions with a global retailer, MenteeBot has been designed to act as the ultimate shopping companion, offering a seamless, natural experience.
Nature Fresh Farms, based in Leamington, Ontario, is one of North America’s largest greenhouse farms growing high-quality organics, berries, peppers, tomatoes, and cucumbers. In 2022, Nature Fresh partnered with Four Growers, a FANUC Authorized System Integrator, to develop a robotic system equipped with AI to harvest tomatoes in the greenhouse environment.
Honeybee Robotics, a Blue Origin company, is developing Lunar Utility Navigation with Advanced Remote Sensing and Autonomous Beaming for Energy Redistribution, also known as LUNARSABER. In July 2024, Honeybee Robotics captured LUNARSABER’s capabilities during a demonstration of a scaled prototype.
In this video we present results of our lab from the latest field deployments conducted in the scope of the Digiforest EU project, in Stein am Rhein, Switzerland. Digiforest brings together various partners working on aerial and legged robots, autonomous harvesters, and forestry decision-makers. The goal of the project is to enable autonomous robot navigation, exploration, and mapping, both below and above the canopy, to create a data pipeline that can support and enhance foresters’ decision-making systems.
I’ll be honest: when I first got this pitch for an autonomous robot dentist, I was like: “Okay, I’m going to talk to these folks and then write an article, because there’s no possible way for this thing to be anything but horrific.” Then they sent me some video that was, in fact, horrific, in the way that only watching a high speed drill remove most of a tooth can be.
But fundamentally this has very little to do with robotics, because getting your teeth drilled just sucks no matter what. So the real question we should be asking is this: How can we make a dental procedure as quick and safe as possible, to minimize that inherent horrific-ness?And the answer, surprisingly, may be this robot from a startup called Perceptive.
Perceptive is today announcing two new technologies that I very much hope will make future dental experiences better for everyone. While it’s easy to focus on the robot here (because, well, it’s a robot), the reason the robot can do what it does (which we’ll get to in a minute) is because of a new imaging system. The handheld imager, which is designed to operate inside of your mouth, uses optical coherence tomography (OCT) to generate a 3D image of the inside of your teeth, and even all the way down below the gum line and into the bone. This is vastly better than the 2D or 3D x-rays that dentists typically use, both in resolution and positional accuracy.
Perceptive’s handheld optical coherence tomography imager scans for tooth decay.Perceptive
X-Rays, it turns out, are actually really bad at detecting cavities; Perceptive CEO Chris Ciriello tells us that the accuracy is on the order of 30 percent of figuring out the location and extent of tooth decay. In practice, this isn’t as much of a problem as it seems like it should be, because the dentist will just start drilling into your tooth and keep going until they find everything. But obviously this won’t work for a robot, where you need all of the data beforehand. That’s where the OCT comes in. You can think of OCT as similar to an ultrasound, in that it uses reflected energy to build up an image, but OCT uses light instead of sound for much higher resolution.
Perceptive’s imager can create detailed 3D maps of the insides of teeth.Perceptive
The reason OCT has not been used for teeth before is because with conventional OCT, the exposure time required to get a detailed image is several seconds, and if you move during the exposure, the image will blur. Perceptive is instead using a structure from motion approach (which will be familiar to many robotics folks), where they’re relying on a much shorter exposure time resulting in far fewer data points, but then moving the scanner and collecting more data to gradually build up a complete 3D image. According to Ciriello, this approach can localize pathology within about 20 micrometers with over 90 percent accuracy, and it’s easy for a dentist to do since they just have to move the tool around your tooth in different orientations until the scan completes.
Again, this is not just about collecting data so that a robot can get to work on your tooth. It’s about better imaging technology that helps your dentist identify and treat issues you might be having. “We think this is a fundamental step change,” Ciriello says. “We’re giving dentists the tools to find problems better.”
The robot is mechanically coupled to your mouth for movement compensation.Perceptive
Ciriello was a practicing dentist in a small mountain town in British Columbia, Canada. People in such communities can have a difficult time getting access to care. “There aren’t too many dentists who want to work in rural communities,” he says. “Sometimes it can take months to get treatment, and if you’re in pain, that’s really not good. I realized that what I had to do was build a piece of technology that could increase the productivity of dentists.”
Perceptive’s robot is designed to take a dental procedure that typically requires several hours and multiple visits, and complete it in minutes in a single visit. The entry point for the robot is crown installation, where the top part of a tooth is replaced with an artificial cap (the crown). This is an incredibly common procedure, and it usually happens in two phases. First, the dentist will remove the top of the tooth with a drill. Next, they take a mold of the tooth so that a crown can be custom fit to it. Then they put a temporary crown on and send you home while they mail the mold off to get your crown made. A couple weeks later, the permanent crown arrives, you go back to the dentist, and they remove the temporary one and cement the permanent one on.
With Perceptive’s system, it instead goes like this: on a previous visit where the dentist has identified that you need a crown in the first place, you’d have gotten a scan of your tooth with the OCT imager. Based on that data, the robot will have planned a drilling path, and then the crown could be made before you even arrive for the drilling to start, which is only possible because the precise geometry is known in advance. You arrive for the procedure, the robot does the actually drilling in maybe five minutes or so, and the perfectly fitting permanent crown is cemented into place and you’re done.
The robot is still in the prototype phase but could be available within a few years.Perceptive
Obviously, safety is a huge concern here, because you’ve got a robot arm with a high-speed drill literally working inside of your skull. Perceptive is well aware of this.
The most important thing to understand about the Perceptive robot is that it’s physically attached to you as it works. You put something called a bite block in your mouth and bite down on it, which both keeps your mouth open and keeps your jaw from getting tired. The robot’s end effector is physically attached to that block through a series of actuated linkages, such that any motions of your head are instantaneously replicated by the end of the drill, even if the drill is moving. Essentially, your skull is serving as the robot’s base, and your tooth and the drill are in the same reference frame. Purely mechanical coupling means there’s no vision system or encoders or software required: it’s a direct physical connection so that motion compensation is instantaneous. As a patient, you’re free to relax and move your head somewhat during the procedure, because it makes no difference to the robot.
Human dentists do have some strategies for not stabbing you with a drill if you move during a procedure, like putting their fingers on your teeth and then supporting the drill on them. But this robot should be safer and more accurate than that method, because of the rigid connection leading to only a few tens of micrometers of error, even on a moving patient. It’ll move a little bit slower than a dentist would, but because it’s only drilling exactly where it needs to, it can complete the procedure faster overall, says Ciriello.
There’s also a physical counterbalance system within the arm, a nice touch that makes the arm effectively weightless. (It’s somewhat similar to the PR2 arm, for you OG robotics folks.) And the final safety measure is the dentist-in-the-loop via a foot pedal that must remain pressed or the robot will stop moving and turn off the drill.
Ciriello claims that not only is the robot able to work faster, it also will produce better results. Most restorations like fillings or crowns last about five years, because the dentist either removed too much material from the tooth and weakened it, or removed too little material and didn’t completely solve the underlying problem. Perceptive’s robot is able to be far more exact. Ciriello says that the robot can cut geometry that’s “not humanly possible,” fitting restorations on to teeth with the precision of custom-machined parts, which is pretty much exactly what they are.
Perceptive has successfully used its robot on real human patients, as shown in this sped-up footage. In reality the robot moves slightly slower than a human dentist.Perceptive
While it’s easy to focus on the technical advantages of Perceptive’s system, dentist Ed Zuckerberg (who’s an investor in Perceptive) points out that it’s not just about speed or accuracy, it’s also about making patients feel better. “Patients think about the precision of the robot, versus the human nature of their dentist,” Zuckerberg says. It gives them confidence to see that their dentist is using technology in their work, especially in ways that can address common phobias. “If it can enhance the patient experience or make the experience more comfortable for phobic patients, that automatically checks the box for me.”
There is currently one other dental robot on the market. Called Yomi, it offers assistive autonomy for one very specific procedure for dental implants. Yomi is not autonomous, but instead provides guidance for a dentist to make sure that they drill to the correct depth and angle.
While Perceptive has successfully tested their first-generation system on humans, it’s not yet ready for commercialization. The next step will likely be what’s called a pivotal clinical trial with the FDA, and if that goes well, Cirello estimates that it could be available to the public in “several years”. Perceptive has raised US $30 million in funding so far, and here’s hoping that’s enough to get them across the finish line.
Elephant Robotics has gone through years of research and development to accelerate its mission of bringing robots to millions of homes and a vision of “Enjoy Robots World”. From the collaborative industrial robots P-series and C-series, which have been on the drawing board since its establishment in 2016, to the lightweight desktop 6 DOF collaborative robot myCobot 280 in 2020, to the dual-armed, semi-humanoid robot myBuddy, which was launched in 2022, Elephant Robotics is launching 3-5 robots per year, and this year’s full-body humanoid robot, the Mercury series, promises to reshape the landscape of non-human workers, introducing intelligent robots like Mercury into research and education and even everyday home environments.
A Commitment to Practical Robotics
Elephant Robotics proudly introduces the Mercury Series, a suite of humanoid robots that not only push the boundaries of innovation but also embody a deep commitment to practical applications. Designed with the future of robotics in mind, the Mercury Series is poised to become the go-to choice for researchers and industry professionals seeking reliable, scalable, and robust solutions.
Elephant Robotics
The Genesis of Mercury Series: Bridging Vision With Practicality
From the outset, the Mercury Series has been envisioned as more than just a collection of advanced prototypes. It is a testament to Elephant Robotics’ dedication to creating humanoid robots that are not only groundbreaking in their capabilities but also practical for mass production and consistent, reliable use in real-world applications.
Mercury X1: Wheeled Humanoid Robot
The Mercury X1 is a versatile wheeled humanoid robot that combines advanced functionalities with mobility. Equipped with dual NVIDIA Jetson controllers, lidar, ultrasonic sensors, and an 8-hour battery life, the X1 is perfect for a wide range of applications, from exploratory studies to commercial tasks requiring mobility and adaptability.
Mercury B1: Dual-Arm Semi-Humanoid Robot
The Mercury B1 is a semi-humanoid robot tailored for sophisticated research. It features 17 degrees of freedom, dual robotic arms, a 9-inch touchscreen, a NVIDIA Xavier control chip, and an integrated 3D camera. The B1 excels in machine vision and VR-assisted teleoperation, and its AI voice interaction and LLM integration mark significant advancements in human-robot communication.
These two advanced models exemplify Elephant Robotics’ commitment to practical robotics. The wheeled humanoid robot Mercury X1 integrates advanced technology with a state-of-the-art mobile platform, ensuring not only versatility but also the feasibility of large-scale production and deployment.
Embracing the Power of Reliable Embodied AI
The Mercury Series is engineered as the ideal hardware platform for embodied AI research, providing robust support for sophisticated AI algorithms and real-world applications. Elephant Robotics demonstrates its commitment to innovation through the Mercury series’ compatibility with NVIDIA’s ISSACSIM, a state-of-the-art simulation platform that facilitates sim2real learning, bridging the gap between virtual environments and physical robot interaction.
The Mercury Series is perfectly suited for the study and experimentation of mainstream large language models in embodied AI. Its advanced capabilities allow seamless integration with the latest AI research. This provides a reliable and scalable platform for exploring the frontiers of machine learning and robotics.
Furthermore, the Mercury Series is complemented by the myArm C650, a teleoperation robotic arm that enables rapid acquisition of physical data. This feature supports secondary learning and adaptation, allowing for immediate feedback and iterative improvements in real-time. These features, combined with the Mercury Series’ reliability and practicality, make it the preferred hardware platform for researchers and institutions looking to advance the field of embodied AI.
The Mercury Series is supported by a rich software ecosystem, compatible with major programming languages, and integrates seamlessly with industry-standard simulation software. This comprehensive development environment is enhanced by a range of auxiliary hardware, all designed with mass production practicality in mind.
Elephant Robotics
Drive to Innovate: Mass Production and Global Benchmarks
The “Power Spring” harmonic drive modules, a hallmark of the Elephant Robotics’ commitment to innovation for mass production, have been meticulously engineered to offer an unparalleled torque-to-weight ratio. These components are a testament to the company’s foresight in addressing the practicalities of large-scale manufacturing. The incorporation of carbon fiber in the design of these modules not only optimizes agility and power but also ensures that the robots are well-prepared for the rigors of the production line and real-world applications. The Mercury Series, with its spirit of innovation, is making a significant global impact, setting a new benchmark for what practical robotics can achieve.
Elephant Robotics is consistently delivering mass-produced robots to a range of renowned institutions and industry leaders, thereby redefining the industry standards for reliability and scalability. The company’s dedication to providing more than mere prototypes is evident in the active role its robots play in various sectors, transforming industries that are in search of dependable and efficient robotic solutions.
Conclusion: The Mercury Series—A Beacon for the Future of Practical Robotics
The Mercury Series represents more than a product; it is a beacon for the future of practical robotics. Elephant Robotics’ dedication to affordability, accessibility, and technological advancement ensures that the Mercury Series is not just a research tool but a platform for real-world impact.
Mercury Usecases | Explore the Capabilities of the Wheeled Humanoid Robot and Discover Its Precision
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The dream of robotic floor care has always been for it to be hands-off and mind-off. That is, for a robot to live in your house that will keep your floors clean without you having to really do anything or even think about it. When it comes to robot vacuuming, that’s been more or less solved thanks to self-emptying robots that transfer debris into docking stations, which iRobot pioneered with the Roomba i7+ in 2018. By 2022, iRobot’s Combo j7+ added an intelligent mopping pad to the mix, which definitely made for cleaner floors but was also a step backwards in the sense that you had to remember to toss the pad into your washing machine and fill the robot’s clean water reservoir every time. The Combo j9+ stuffed a clean water reservoir into the dock itself, which could top off the robot with water by itself for a month.
With the new Roomba Combo 10 Max, announced today, iRobot has cut out (some of) that annoying process thanks to a massive new docking station that self-empties vacuum debris, empties dirty mop water, refills clean mop water, and then washes and dries the mopping pad, completely autonomously.
iRobot
The Roomba part of this is a mildly upgraded j7+, and most of what’s new on the hardware side here is in the “multifunction AutoWash Dock.” This new dock is a beast: It empties the robot of all of the dirt and debris picked up by the vacuum, refills the Roomba’s clean water tank from a reservoir, and then starts up a wet scrubby system down under the bottom of the dock. The Roomba deploys its dirty mopping pad onto that system, and then drives back and forth while the scrubby system cleans the pad. All the dirty water from this process gets sucked back up into a dedicated reservoir inside the dock, and the pad gets blow-dried while the scrubby system runs a self-cleaning cycle.
The dock removes debris from the vacuum, refills it with clean water, and then uses water to wash the mopping pad.iRobot
This means that as a user, you’ve only got to worry about three things: dumping out the dirty water tank every week (if you use the robot for mopping most days), filling the clean water tank every week, and then changing out the debris every two months. That is not a lot of hands-on time for having consistently clean floors.
The other thing to keep in mind about all of these robots is that they do need relatively frequent human care if you want them to be happy and successful. That means flipping them over and getting into their guts to clean out the bearings and all that stuff. iRobot makes this very easy to do, and it’s a necessary part of robot ownership, so the dream of having a robot that you can actually forget completely is probably not achievable.
The consequence for this convenience is a real chonker of a dock. The dock is basically furniture, and to the company’s credit, iRobot designed it so that the top surface is useable as a shelf—Access to the guts of the dock are from the front, not the top. This is fine, but it’s also kind of crazy just how much these docks have expanded, especially once you factor in the front ramp that the robot drives up, which sticks out even farther.
The Roomba will detect carpet and lift its mopping pad up to prevent drips.iRobot
We asked iRobot director of project management Warren Fernandez about whether docks are just going to keep on getting bigger forever until we’re all just living in giant robot docks, to which he said: “Are you going to continue to see some large capable multifunction docks out there in the market? Yeah, I absolutely think you will—but when does big become too big?” Fernandez says that there are likely opportunities to reduce dock size going forward through packaging efficiencies or dual-purpose components, but that there’s another option, too: Distributed docks. “If a robot has dry capabilities and wet capabilities, do those have to coexist inside the same chassis? What if they were separate?” says Fernandez.
We should mention that iRobot is not the first in the robotic floor care robot space to have a self-cleaning mop, and it’s also not the first to think about distributed docks, although as Fernandez explains, this is a more common approach in Asia where you can also take advantage of home plumbing integration. “It’s a major trend in China, and starting to pop up a little bit in Europe, but not really in North America yet. How amazing could it be if you had a dock that, in a very easy manner, was able to tap right into plumbing lines for water supply and sewage disposal?”
According to Fernandez, this tends to be much easier to do in China, both because the labor cost for plumbing work is far lower than in the United States and Europe, and also because it’s fairly common for apartments in China to have accessible floor drains. “We don’t really yet see it in a major way at a global level,” Fernandez tells us. “But that doesn’t mean it’s not coming.”
The robot autonomously switches mopping mode on and off for different floor surfaces.iRobot
We should also mention the Roomba Combo 10 Max, which includes some software updates:
The front-facing camera and specialized bin sensors can identify dirtier areas eight times as effectively as before.
The Roomba can identify specific rooms and prioritize the order they’re cleaned in, depending on how dirty they get.
A new cleaning behavior called “Smart Scrub” adds a back-and-forth scrubbing motion for floors that need extra oomph.
And here’s what I feel like the new software should do, but doesn’t:
Use the front-facing camera and bin sensors to identify dirtier areas and then autonomously develop a schedule to more frequently clean those areas.
Activate Smart Scrub when the camera and bin sensors recognize an especially dirty floor.
I say “should do” because the robot appears to be collecting the data that it needs to do these things but it doesn’t do them yet. New features (especially new features that involve autonomy) take time to develop and deploy, but imagine a robot that makes much more nuanced decisions about where and when to clean based on very detailed real-time data and environmental understanding that iRobot has already implemented.
I also appreciate that even as iRobot is emphasizing autonomy and leveraging data to start making more decisions for the user, the company is also making sure that the user has as much control as possible through the app. For example, you can set the robot to mop your floor without vacuuming first, even though if you do that, all you’re going to end up with a much dirtier mop. Doesn’t make a heck of a lot of sense, but if that’s what you want, iRobot has empowered you to do it.
The dock opens from the front for access to the clean- and dirty-water storage and the dirt bag.iRobot
The Roomba Combo 10 Max will be launching in August for US $1,400. That’s expensive, but it’s also how iRobot does things: A new Roomba with new tech always gets flagship status and premium cost. Sooner or later it’ll be affordable enough that the rest of us will be able to afford it, too.
Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.
ICRA@40: 23–26 September 2024, ROTTERDAM, NETHERLANDS
Perching with winged Unmanned Aerial Vehicles has often been solved by means of complex control or intricate appendages. Here, we present a method that relies on passive wing morphing for crash-landing on trees and other types of vertical poles. Inspired by the adaptability of animals’ and bats’ limbs in gripping and holding onto trees, we design dual-purpose wings that enable both aerial gliding and perching on poles.
Pretty impressive to have low enough latency in controlling your robot’s hardware that it can play ping pong, although it makes it impossible to tell whether the robot or the human is the one that’s actually bad at the game.
Have you ever wondered how insects are able to go so far beyond their home and still find their way? The answer to this question is not only relevant to biology but also to making the AI for tiny, autonomous robots. We felt inspired by biological findings on how ants visually recognize their environment and combine it with counting their steps in order to get safely back home.
Team RoMeLa Practice with ARTEMIS humanoid robots, featuring Tsinghua Hephaestus (Booster Alpha). Fully autonomous humanoid robot soccer match with the official goal of beating the human WorldCup Champions by the year 2050.
We propose RialTo, a new system for robustifying real-world imitation learning policies via reinforcement learning in “digital twin” simulation environments constructed on the fly from small amounts of real-world data.
There is absolutely no reason to watch this entire video, but Moley Robotics is still working on that robotic kitchen of theirs.
I will once again point out that the hardest part of cooking (for me, anyway) is the prep and the cleanup, and this robot still needs you to do all that.
B-Human has so far won 10 titles at the RoboCup SPL tournament. Can we make it 11 this year? Our RoboCup starts off with a banger game against HTWK Robots form Leipzig!
AMBIDEX is a dual-armed robot with an innovative mechanism developed for safe coexistence with humans. Based on an innovative cable structure, it is designed to be both strong and stable.
As NASA’s Perseverance rover prepares to ascend to the rim of Jezero Crater, its team is investigating a rock unlike any that they’ve seen so far on Mars. Deputy project scientist Katie Stack Morgan explains why this rock, found in an ancient channel that funneled water into the crater, could be among the oldest that Perseverance has investigated—or the youngest.
We present a novel approach for enhancing human-robot collaboration using physical interactions for real-time error correction of large language model (LLM) parameterized commands.
Husky Observer was recently used to autonomously inspect solar panels at a large solar panel farm. As part of its mission, the robot navigated rows of solar panels, stopping to inspect areas with its integrated thermal camera. Images were taken by the robot and enhanced to detect potential “hot spots” in the panels.
Meet Hydrus, the autonomous underwater drone revolutionising underwater data collection by eliminating the barriers to its entry. Hydrus ensures that even users with limited resources can execute precise and regular subsea missions to meet their data requirements.
Cigarette butts are the second most common undisposed-of litter on Earth—of the six trillion-ish cigarettes inhaled every year, it’s estimated that over 4 trillion of the butts are just tossed onto the ground, each one leeching over 700 different toxic chemicals into the environment. Let’s not focus on the fact that all those toxic chemicals are also going into people’s lungs, and instead talk about the ecosystem damage that they can do and also just the general grossness of having bits of sucked-on trash everywhere. Ew.
Preventing those cigarette butts from winding up on the ground in the first place would be the best option, but it would require a pretty big shift in human behavior. Operating under the assumption that humans changing their behavior is a nonstarter, roboticists from the Dynamic Legged Systems unit at the Italian Institute of Technology (IIT), in Genoa, have instead designed a novel platform for cigarette-butt cleanup in the form of a quadrupedal robot with vacuums attached to its feet.
IIT
There are, of course, far more efficient ways of at least partially automating the cleanup of litter with machines. The challenge is that most of that automation relies on mobility systems with wheels, which won’t work on the many beautiful beaches (and many beautiful flights of stairs) of Genoa. In places like these, it still falls to humans to do the hard work, which is less than ideal.
This robot, developed in Claudio Semini’s lab at IIT, is called VERO (Vacuum-cleaner Equipped RObot). It’s based around an AlienGo from Unitree, with a commercial vacuum mounted on its back. Hoses go from the vacuum down the leg to each foot, with a custom 3D-printed nozzle that puts as much suction near the ground as possible without tripping the robot up. While the vacuum is novel, the real contribution here is how the robot autonomously locates things on the ground and then plans how to interact with those things using its feet.
First, an operator designates an area for VERO to clean, after which the robot operates by itself. After calculating an exploration path to explore the entire area, the robot uses its onboard cameras and a neural network to detect cigarette butts. This is trickier than it sounds, because there may be a lot of cigarette butts on the ground, and they all probably look pretty much the same, so the system has to filter out all of the potential duplicates. The next step is to plan its next steps: VERO has to put the vacuum side of one of its feet right next to each cigarette butt while calculating a safe, stable pose for the rest of its body. Since this whole process can take place on sand or stairs or other uneven surfaces, VERO has to prioritize not falling over before it decides how to do the collection. The final collecting maneuver is fine-tuned using an extra Intel RealSense depth camera mounted on the robot’s chin.
VERO has been tested successfully in six different scenarios that challenge both its locomotion and detection capabilities.IIT
Initial testing with the robot in a variety of different environments showed that it could successfully collect just under 90 percent of cigarette butts, which I bet is better than I could do, and I’m also much more likely to get fed up with the whole process. The robot is not very quick at the task, but unlike me it will never get fed up as long as it’s got energy in its battery, so speed is somewhat less important.
As far as the authors of this paper are aware (and I assume they’ve done their research), this is “the first time that the legs of a legged robot are concurrently utilized for locomotion and for a different task.” This is distinct from other robots that can (for example) open doors with their feet, because those robots stop using the feet as feet for a while and instead use them as manipulators.
So, this is about a lot more than cigarette butts, and the researchers suggest a variety of other potential use cases, including spraying weeds in crop fields, inspecting cracks in infrastructure, and placing nails and rivets during construction.
Some use cases include potentially doing multiple things at the same time, like planting different kinds of seeds, using different surface sensors, or driving both nails and rivets. And since quadrupeds have four feet, they could potentially host four completely different tools, and the software that the researchers developed for VERO can be slightly modified to put whatever foot you want on whatever spot you need.
Food prep is one of those problems that seems like it should be solvable by robots. It’s a predictable, repetitive, basic manipulation task in a semi-structured environment—seems ideal, right? And obviously there’s a huge need, because human labor is expensive and getting harder and harder to find in these contexts. There are currently over a million unfilled jobs in the food industry in the United States, and even with jobs that are filled, the annual turnover rate is 150 percent (meaning a lot of workers don’t even last a year).
Food prep seems like a great opportunity for robots, which is why Chef Robotics and a handful of other robotics companies tackled it a couple years ago by bringing robots to fast casual restaurants like Chipotle or Sweetgreen, where you get served a custom-ish meal from a selection of ingredients at a counter.
But this didn’t really work out, for a couple of reasons. First, doing things that are mostly effortless for humans are inevitably extremely difficult for robots. And second, humans actually do a lot of useful things in a restaurant context besides just putting food onto plates, and the robots weren’t up for all of those things.
Still, Chef Robotics founder and CEO Rajat Bhageria wasn’t ready to let this opportunity go. “The food market is arguably the biggest market that’s tractable for AI today,” he told IEEE Spectrum. And with a bit of a pivot away from the complicated mess of fast casual restaurants, Chef Robotics has still managed to prepare over 20 million meals thanks to autonomous robot arms deployed all over North America. Without knowing it, you may even have eaten such a meal.
“The hard thing is, can you pick fast? Can you pick consistently? Can you pick the right portion size without spilling? And can you pick without making it look like the food was picked by a machine?” —Rajat Bhageria, Chef Robotics
When we spoke with Bhageria, he explained that there are three basic tasks involved in prepared food production: prep (tasks like chopping ingredients), the actual cooking process, and then assembly (or plating). Of these tasks, prep scales pretty well with industrial automation in that you can usually order pre-chopped or mixed ingredients, and cooking also scales well since you can cook more with only a minimal increase in effort just by using a bigger pot or pan or oven. What doesn’t scale well is the assembly, especially when any kind of flexibility or variety is required. You can clearly see this in action at any fast casual restaurant, where a couple of people are in the kitchen cooking up massive amounts of food while each customer gets served one at a time.
So with that bottleneck identified, let’s throw some robots at the problem, right? And that’s exactly what Chef Robotics did, explains Bhageria: “we went to our customers, who said that their biggest pain point was labor, and the most labor is in assembly, so we said, we can help you solve this.”
Chef Robotics started with fast casual restaurants. They weren’t the first to try this—many other robotics companies had attempted this before, with decidedly mixed results.“We actually had some good success in the early days selling to fast casual chains,” Bhageria says, “but then we had some technical obstacles. Essentially, if we want to have a human-equivalent system so that we can charge a human-equivalent service fee for our robot, we need to be able to do every ingredient. You’re either a full human equivalent, or our customers told us it wouldn’t be useful.”
Part of the challenge is that training robots do perform all of the different manipulations required for different assembly tasks requires different kinds of real world data. That data simply doesn’t exist—or, if it does, any company that has it knows what it’s worth and isn’t sharing. You can’t easily simulate this kind of data, because food can be gross and difficult to handle, whether it’s gloopy or gloppy or squishy or slimy or unpredictably deformable in some other way, and you really need physical experience to train a useful manipulation model.
Setting fast casual restaurants aside for a moment, what about food prep situations where things are as predictable as possible, like mass-produced meals? We’re talking about food like frozen dinners, that have a handful of discrete ingredients packed into trays at factory scale. Frozen meal production relies on automation rather than robotics because the scale is such that the cost of dedicated equipment can be justified.
There’s a middle ground, though, where robots have found (some) opportunity: When you need to produce a high volume of the same meal, but that meal changes regularly. For example, think of any kind of pre-packaged meal that’s made in bulk, just not at frozen-food scale. It’s an opportunity for automation in a structured environment—but with enough variety that actual automation isn’t cost effective. Suddenly, robots and their tiny bit of flexible automation have a chance to be a practical solution.
“We saw these long assembly lines, where humans were scooping food out of big tubs and onto individual trays,” Bhageria says. “They do a lot of different meals on these lines; it’s going to change over and they’re going to do different meals throughout the week. But at any given moment, each person is doing one ingredient, and maybe on a weekly basis, that person would do six ingredients. This was really compelling for us because six ingredients is something we can bootstrap in a lab. We can get something good enough and if we can get something good enough, then we can ship a robot, and if we can ship a robot to production, then we will get real world training data.”
Chef Robotics has been deploying robot modules that they can slot into existing food assembly lines in place of humans without any retrofitting necessary. The modules consist of six degree of freedom arms wearing swanky IP67 washable suits. To handle different kinds of food, the robots can be equipped with a variety of different utensils (and their accompanying manipulation software strategies). Sensing includes a few depth cameras, as well as a weight-sensing platform for the food tray to ensure consistent amounts of food are picked. And while arms with six degrees of freedom may be overkill for now, eventually the hope is that they’ll be able to handle more complex food like asparagus, where you need to do a little bit more than just scoop.
While Chef Robotics seems to have a viable business here, Bhageria tells us that he keeps coming back to that vision of robots being useful in fast casual restaurants, and eventually, robots making us food in our homes. Making that happen will require time, experience, technical expertise, and an astonishing amount of real-world training data, which is the real value behind those 20 million robot-prepared meals (and counting). The more robots the company deploys, the more data they collect, which will allow them to train their food manipulation models to handle a wider variety of ingredients to open up even more deployments. Their robots, Chef’s website says, “essentially act as data ingestion engines to improve our AI models.”
The next step is likely ghost kitchens where the environment is still somewhat controlled and human interaction isn’t necessary, followed by deployments in commercial kitchens more broadly. But even that won’t be enough for Bhageria, who wants robots that can take over from all of the drudgery in food service: “I’m really excited about this vision,” he says. “How do we deploy hundreds of millions of robots all over the world that allow humans to do what humans do best?”
Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.
RoboCup 2024: 17–22 July 2024, EINDHOVEN, NETHERLANDS
ICRA@40: 23–26 September 2024, ROTTERDAM, NETHERLANDS
Figure is making progress toward a humanoid robot that can do something useful, but keep in mind that the “full use case” here is not one continuous shot.
One of those things that’s a lot harder for robots than it probably looks.
This is a demo of hammering a nail. The instantaneous rebound force from the hammer is absorbed through a combination of the elasticity of the rubber material securing the hammer, the deflection in torque sensors and harmonic gears, back-drivability, and impedance control. This allows the nail to be driven with a certain amount of force.
Although bin packing has been a key benchmark task for robotic manipulation, the community has mainly focused on the placement of rigid rectilinear objects within the container. We address this by presenting a soft robotic hand that combines vision, motor-based proprioception, and soft tactile sensors to identify, sort, and pack a stream of unknown objects.
Status Update: Extending traditional visual servo and compliant control by integrating the latest reinforcement and imitation learning control methodologies, UBTECH gradually trains the embodied intelligence-based “cerebellum” of its humanoid robot Walker S for diverse industrial manipulation tasks.
The Robotic Systems Lab participated in the Advanced Industrial Robotic Applications (AIRA) Challenge at the ACHEMA 2024 process industry trade show, where teams demonstrated their teleoperated robotic solutions for industrial inspection tasks. We competed with the ALMA legged manipulator robot, teleoperated using a second robot arm in a leader-follower configuration, placing us in third place for the competition.
Using a new type of surgical intervention and neuroprosthetic interface, MIT researchers, in collaboration with colleagues from Brigham and Women’s Hospital, have shown that a natural walking gait is achievable using a prosthetic leg fully driven by the body’s own nervous system. The surgical amputation procedure reconnects muscles in the residual limb, which allows patients to receive “proprioceptive” feedback about where their prosthetic limb is in space.
Coal mining in Forest of Dean (UK) is such a difficult and challenging job. Going into the mine as human is sometimes almost impossible. We did it with our robot while inspecting the mine with our partners (Forestry England) and the local miners!
Would you tango with a robot? Inviting us into the fascinating world of dancing machines, robot choreographer Catie Cuan highlights why teaching robots to move with grace, intention and emotion is essential to creating AI-powered machines we will want to welcome into our daily lives.
It may at times seem like there are as many humanoid robotics companies out there as the industry could possibly sustain, but the potential for useful and reliable and affordable humanoids is so huge that there’s plenty of room for any company that can actually get them to work. Joining the dozen or so companies already on this quest is
Persona AI, founded last month by Nic Radford and Jerry Pratt, two people who know better than just about anyone what it takes to make a successful robotics company, although they also know enough to be wary of getting into commercial humanoids.
Persona AI may not be the first humanoid robotics startup, but its founders have some serious experience in the space:
Nic Radford lead the team that developed NASA’s Valkyrie humanoid robot, before founding Houston Mechatronics (now Nauticus Robotics), which introduced a transforming underwater robot in 2019. He also founded Jacobi Motors, which is commercializing variable flux electric motors.
“It took me a long time to warm up to this idea,” Nic Radford tells us. “After I left Nauticus in January, I didn’t want anything to do with humanoids, especially underwater humanoids, and I didn’t even want to hear the word ‘robot.’ But things are changing so quickly, and I got excited and called Jerry and I’m like, this is actually very possible.” Jerry Pratt, who recently left Figure due primarily to the
two-body problem, seems to be coming from a similar place: “There’s a lot of bashing your head against the wall in robotics, and persistence is so important. Nic and I have both gone through pessimism phases with our robots over the years. We’re a bit more optimistic about the commercial aspects now, but we want to be pragmatic and realistic about things too.”
Behind all of the recent humanoid hype lies the very, very difficult problem of making a highly technical piece of hardware and software compete effectively with humans in the labor market. But that’s also a very, very big opportunity—big enough that Persona doesn’t have to be the first company in this space, or the best funded, or the highest profile. They simply have to succeed, but of course sustainable commercial success with any robot (and bipedal robots in particular) is anything but simple. Step one will be building a founding team across two locations: Houston and Pensacola, Fla. But Radford says that the response so far to just a couple of
LinkedIn posts about Persona has been “tremendous.” And with a substantial seed investment in the works, Persona will have more than just a vision to attract top talent.
For more details about Persona, we spoke with Persona AI co-founders Nic Radford and Jerry Pratt.
Why start this company, why now, and why you?
Nic Radford
Nic Radford: The idea for this started a long time ago. Jerry and I have been working together off and on for quite a while, being in this field and sharing a love for what the humanoid potential is while at the same time being frustrated by where humanoids are at. As far back as probably 2008, we were thinking about starting a humanoids company, but for one reason or another the viability just wasn’t there. We were both recently searching for our next venture and we couldn’t imagine sitting this out completely, so we’re finally going to explore it, although we know better than anyone that robots are really hard. They’re not that hard to build; but they’re hard to make useful and make money with, and the challenge for us is whether we can build a viable business with Persona: can we build a business that uses robots and makes money? That’s our singular focus. We’re pretty sure that this is likely the best time in history to execute on that potential.
Jerry Pratt: I’ve been interested in commercializing humanoids for quite a while—thinking about it, and giving it a go here and there, but until recently it has always been the wrong time from both a commercial point of view and a technological readiness point of view. You can think back to the DARPA Robotics Challenge days when we had to wait about 20 seconds to get a good lidar scan and process it, which made it really challenging to do things autonomously. But we’ve gotten much, much better at perception, and now, we can get a whole perception pipeline to run at the framerate of our sensors. That’s probably the main enabling technology that’s happened over the last 10 years.
From the commercial point of view, now that we’re showing that this stuff’s feasible, there’s been a lot more pull from the industry side. It’s like we’re at the next stage of the Industrial Revolution, where the harder problems that weren’t roboticized from the 60s until now can now be. And so, there’s really good opportunities in a lot of different use cases.
A bunch of companies have started within the last few years, and several were even earlier than that. Are you concerned that you’re too late?
Radford: The concern is that we’re still too early! There might only be one Figure out there that raises a billion dollars, but I don’t think that’s going to be the case. There’s going to be multiple winners here, and if the market is as large as people claim it is, you could see quite a diversification of classes of commercial humanoid robots.
Jerry Pratt
Pratt: We definitely have some catching up to do but we should be able to do that pretty quickly, and I’d say most people really aren’t that far from the starting line at this point. There’s still a lot to do, but all the technology is here now—we know what it takes to put together a really good team and to build robots. We’re also going to do what we can to increase speed, like by starting with a surrogate robot from someone else to get the autonomy team going while building our own robot in parallel.
Radford: I also believe that our capital structure is a big deal. We’re taking an anti-stealth approach, and we want to bring everyone along with us as our company grows and give out a significant chunk of the company to early joiners. It was an anxiety of ours that we would be perceived as a me-too and that nobody was going to care, but it’s been the exact opposite with a compelling response from both investors and early potential team members.
So your approach here is not to look at all of these other humanoid robotics companies and try and do something they’re not, but instead to pursue similar goals in a similar way in a market where there’s room for all?
Pratt: All robotics companies, and AI companies in general, are standing on the shoulders of giants. These are the thousands of robotics and AI researchers that have been collectively bashing their heads against the myriad problems for decades—some of the first humanoids were walking at
Waseda University in the late 1960s. While there are some secret sauces that we might bring to the table, it is really the combined efforts of the research community that now enables commercialization.
So if you’re at a point where you need something new to be invented in order to get to applications, then you’re in trouble, because with invention you never know how long it’s going to take. What is available today and now, the technology that’s been developed by various communities over the last 50+ years—we all have what we need for the first three applications that are widely mentioned: warehousing, manufacturing, and logistics. The big question is, what’s the fourth application? And the fifth and the sixth? And if you can start detecting those and planning for them, you can get a leg up on everybody else.
The difficulty is in the execution and integration. It’s a ten thousand—no, that’s probably too small—it’s a hundred thousand piece puzzle where you gotta get each piece right, and occasionally you lose some pieces on the floor that you just can’t find. So you need a broad team that has expertise in like 30 different disciplines to try to solve the challenge of an end-to-end labor solution with humanoid robots.
Radford: The idea is like one percent of starting a company. The rest of it, and why companies fail, is in the execution. Things like, not understanding the market and the product-market fit, or not understanding how to run the company, the dimensions of the actual business. I believe we’re different because with our backgrounds and our experience we bring a very strong view on execution, and that is our focus on day one. There’s enough interest in the VC community that we can fund this company with a singular focus on commercializing humanoids for a couple different verticals.
But listen, we got some novel ideas in actuation and other tricks up our sleeve that might be very compelling for this, but we don’t want to emphasize that aspect. I don’t think Persona’s ultimate success comes just from the tech component. I think it comes mostly from ‘do we understand the customer, the market needs, the business model, and can we avoid the mistakes of the past?’
How is that going to change things about the way that you run Persona?
Radford: I started a company [Houston Mechatronics] with a bunch of research engineers. They don’t make the best product managers. More broadly, if you’re staffing all your disciplines with roboticists and engineers, you’ll learn that it may not be the most efficient way to bring something to market. Yes, we need those skills. They are essential. But there’s so many other aspects of a business that get overlooked when you’re fundamentally a research lab trying to commercialize a robot. I’ve been there, I’ve done that, and I’m not interested in making that mistake again.
Pratt: It’s important to get a really good product team that’s working with a customer from day one to have customer needs drive all the engineering. The other approach is ‘build it and they will come’ but then maybe you don’t build the right thing. Of course, we want to build multi-purpose robots, and we’re steering clear of saying ‘general purpose’ at this point. We don’t want to overfit to any one application, but if we can get to a dozen use cases, two or three per customer site, then we’ve got something.
There still seems to be a couple of unsolved technical challenges with humanoids, including hands, batteries, and safety. How will Persona tackle those things?
Pratt: Hands are such a hard thing—getting a hand that has the required degrees of freedom and is robust enough that if you accidentally hit it against your table, you’re not just going to break all your fingers. But we’ve seen robotic hand companies popping up now that are showing videos of hitting their hands with a hammer, so I’m hopeful.
Getting one to two hours of battery life is relatively achievable. Pushing up towards five hours is super hard. But batteries can now be charged in 20 minutes or so, as long as you’re going from 20 percent to 80 percent. So we’re going to need a cadence where robots are swapping in and out and charging as they go. And batteries will keep getting better.
Radford: We do have a focus on safety. It was paramount at NASA, and when we were working on Robonaut, it led to a lot of morphological considerations with padding. In fact, the first concepts and images we have of our robot illustrate extensive padding, but we have to do that carefully, because at the end of the day it’s mass and it’s inertia.
What does the near future look like for you?
Pratt: Building the team is really important—getting those first 10 to 20 people over the next few months. Then we’ll want to get some hardware and get going really quickly, maybe buying a couple of robot arms or something to get our behavior and learning pipelines going while in parallel starting our own robot design. From our experience, after getting a good team together and starting from a clean sheet, a new robot takes about a year to design and build. And then during that period we’ll be securing a customer or two or three.
Radford: We’re also working hard on some very high profile partnerships that could influence our early thinking dramatically. Like Jerry said earlier, it’s a massive 100,000 piece puzzle, and we’re working on the fundamentals: the people, the cash, and the customers.
One of the (many) great things about robots is that they don’t have to be constrained by how their biological counterparts do things. If you have a particular problem your robot needs to solve, you can get creative with extra sensors: many quadrupeds have side cameras and butt cameras for obstacle avoidance, and humanoids sometimes have chest cameras and knee cameras to help with navigation along with wrist cameras for manipulation. But how far can you take this? I have no idea, but it seems like we haven’t gotten to the end of things yet because now there’s a quadruped with cameras on the bottom of its feet.
Sensorized feet is not a new idea; it’s pretty common for quadrupedal robots to have some kind of foot-mounted force sensor to detect ground contact. Putting an actual camera down there is fairly novel, though, because it’s not at all obvious how you’d go about doing it. And the way that roboticists from the Southern University of Science and Technology in Shenzhen went about doing it is, indeed, not at all obvious.
Go1’s snazzy feetsies have soles made of transparent acrylic, with slightly flexible plastic structure supporting a 60 millimeter gap up to each camera (640x480 at 120 frames per second) with a quartet of LEDs to provide illumination. While it’s complicated looking, at 120 grams, it doesn’t weigh all that much, and costs only about $50 per foot ($42 of which is the camera). The whole thing is sealed to keep out dirt and water.
So why bother with all of this (presumably somewhat fragile) complexity? As we ask quadruped robots to do more useful things in more challenging environments, having more information about what exactly they’re stepping on and how their feet are interacting with the ground is going to be super helpful. Robots that rely only on proprioceptive sensing (sensing self-movement) are great and all, but when you start trying to move over complex surfaces like sand, it can be really helpful to have vision that explicitly shows how your robot is interacting with the surface that it’s stepping on. Preliminary results showed that Foot Vision enabled the Go1 using it to perceive the flow of sand or soil around its foot as it takes a step, which can be used to estimate slippage, the bane of ground-contacting robots.
The researchers acknowledge that their hardware could use a bit of robustifying, and they also want to try adding some tread patterns around the circumference of the foot, since that plexiglass window is pretty slippery. The overall idea is to make Foot Vision as useful as the much more common gripper-integrated vision systems for robotic manipulation, helping legged robots make better decisions about how to get where they need to go.
Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.
RoboCup 2024: 17–22 July 2024, EINDHOVEN, NETHERLANDS
ICRA@40: 23–26 September 2024, ROTTERDAM, NETHERLANDS
Agility has been working with GXO for a bit now, but the big news here (and it IS big news) is that Agility’s Digit robots at GXO now represent the first formal commercial deployment of humanoid robots.
In this paper, we introduce a full-stack system for humanoids to learn motion and autonomous skills from human data. Through shadowing, human operators can teleoperate humanoids to collect whole-body data for learning different tasks in the real world. Using the data collected, we then perform supervised behavior cloning to train skill policies using egocentric vision, allowing humanoids to complete different tasks autonomously by imitating human skills.
Meet CARMEN, short for Cognitively Assistive Robot for Motivation and Neurorehabilitation–a small, tabletop robot designed to help people with mild cognitive impairment (MCI) learn skills to improve memory, attention, and executive functioning at home.
This is a demo of cutting wood with a saw. When using position control for this task, precise measurement of the cutting amount is necessary. However, by using impedance control, this requirement is eliminated, allowing for successful cutting with only rough commands.
Our Skunk Works team developed a modified version of the SR-71 Blackbird, titled the M-21, which carried an uncrewed reconnaissance drone called the D-21. The D-21 was designed to capture intelligence, release its camera, then self-destruct!
Field AI’s brain technology is enabling robots to autonomously explore oil and gas facilities, navigating throughout the site and inspecting equipment for anomalies and hazardous conditions.
Husky Observer was recently deployed at a busy automotive rail yard to carry out various autonomous inspection tasks including measuring train car positions and RFID data collection from the offloaded train inventory.
Would you swallow a micro-robot? In a gutsy demo, physician Vivek Kumbhari navigates Pillbot, a wireless, disposable robot swallowed onstage by engineer Alex Luebke, modeling how this technology can swiftly provide direct visualization of internal organs. Learn more about how micro-robots could move us past the age of invasive endoscopies and open up doors to more comfortable, affordable medical imaging.
How will AI improve our lives in the years to come? From its inception six decades ago to its recent exponential growth, futurist Ray Kurzweil highlights AI’s transformative impact on various fields and explains his prediction for the singularity: the point at which human intelligence merges with machine intelligence.
Insects have long been an inspiration for robots. The insect world is full of things that are tiny, fully autonomous, highly mobile, energy efficient, multimodal, self-repairing, and I could go on and on but you get the idea—insects are both an inspiration and a source of frustration to roboticists because it’s so hard to get robots to have anywhere close to insect capability.
We’re definitely making progress, though. In a paper published last month in IEEE Robotics and Automation Letters, roboticists from Shanghai Jong Tong University demonstrated the most buglike robotic bug I think I’ve ever seen.
Okay so it may not look the most buglike, but it can do many very buggy bug things, including crawling, taking off horizontally, flying around (with six degrees of freedom control), hovering, landing, and self-righting if necessary. JT-fly weighs about 35 grams and has a wingspan of 33 centimeters, using four wings at once to fly at up to 5 meters per second and six legs to scurry at 0.3 m/s. Its 380 milliampere-hour battery powers it for an actually somewhat useful 8-ish minutes of flying and about 60 minutes of crawling.
While that amount of endurance may not sound like a lot, robots like these aren’t necessarily intended to be moving continuously. Rather, they move a little bit, find a nice safe perch, and then do some sensing or whatever until you ask them to move to a new spot. Ideally, most of that movement would be crawling, but having the option to fly makes JT-fly exponentially more useful.
Or, potentially more useful, because obviously this is still very much a research project. It does seem like there’s a bunch more optimization that could be done here. For example, JT-fly uses completely separate systems for flying and crawling, with two motors powering the legs and two additional motors powering the wings—plus two wing servos for control. There’s currently a limited amount of onboard autonomy, with an inertial measurement unit, barometer, and wireless communication, but otherwise not much in the way of useful payload.
Insects are both an inspiration and a source of frustration to roboticists because it’s so hard to get robots to have anywhere close to insect capability.
It won’t surprise you to learn that the researchers have disaster-relief applications in mind for this robot, suggesting that “after natural disasters such as earthquakes and mudslides, roads and buildings will be severely damaged, and in these scenarios, JT-fly can rely on its flight ability to quickly deploy into the mission area.” One day, robots like these will actually be deployed for disaster relief, and although that day is not today, we’re just a little bit closer than we were before.
Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.
RoboCup 2024: 17–22 July 2024, EINDHOVEN, NETHERLANDS
Do you have trouble multitasking? Cyborgize yourself through muscle stimulation to automate repetitive physical tasks while you focus on something else.
By combining a 5,000 frame-per-second (FPS) event camera with a 20-FPS RGB camera, roboticists from the University of Zurich have developed a much more effective vision system that keeps autonomous cars from crashing into stuff, as described in the current issue of Nature.
Mitsubishi Electric has been awarded the GUINNESS WORLD RECORDS title for the fastest robot to solve a puzzle cube. The robot’s time of 0.305 second beat the previous record of 0.38 second, for which it received a GUINNESS WORLD RECORDS certificate on 21 May 2024.
Sony’s AIBO is celebrating its 25th anniversary, which seems like a long time, and it is. But back then, the original AIBO could check your email for you. Email! In 1999!
MIT CSAIL researchers enhance robotic precision with sophisticated tactile sensors in the palm and agile fingers, setting the stage for improvements in human-robot interaction and prosthetic technology.
We present a novel adversarial attack method designed to identify failure cases in any type of locomotion controller, including state-of-the-art reinforcement-learning-based controllers. Our approach reveals the vulnerabilities of black-box neural network controllers, providing valuable insights that can be leveraged to enhance robustness through retraining.
In this work, we investigate a novel integrated flexible OLED display technology used as a robotic skin-interface to improve robot-to-human communication in a real industrial setting at Volkswagen or a collaborative human-robot interaction task in motor assembly. The interface was implemented in a workcell and validated qualitatively with a small group of operators (n=9) and quantitatively with a large group (n=42). The validation results showed that using flexible OLED technology could improve the operators’ attitude toward the robot; increase their intention to use the robot; enhance their perceived enjoyment, social influence, and trust; and reduce their anxiety.
We introduce InflatableBots, shape-changing inflatable robots for large-scale encountered-type haptics in VR. Unlike traditional inflatable shape displays, which are immobile and limited in interaction areas, our approach combines mobile robots with fan-based inflatable structures. This enables safe, scalable, and deployable haptic interactions on a large scale.
We present a bioinspired passive dynamic foot in which the claws are actuated solely by the impact energy. Our gripper simultaneously resolves the issue of smooth absorption of the impact energy and fast closure of the claws by linking the motion of an ankle linkage and the claws through soft tendons.
In this video, a 3-UPU exoskeleton robot for a wrist joint is designed and controlled to perform wrist extension, flexion, radial-deviation, and ulnar-deviation motions in stroke-affected patients. This is the first time a 3-UPU robot has been used effectively for any kind of task.
“UPU” stands for “universal-prismatic-universal” and refers to the actuators—the prismatic joints between two universal joints.
In this paper, we propose a system for the artist-directed authoring of stylized bipedal walking gaits, tailored for execution on robotic characters. To demonstrate the utility of our approach, we animate gaits for a custom, free-walking robotic character, and show, with two additional in-simulation examples, how our procedural animation technique generalizes to bipeds with different degrees of freedom, proportions, and mass distributions.
The European drone project Labyrinth aims to keep new and conventional air traffic separate, especially in busy airspaces such as those expected in urban areas. The project provides a new drone-traffic service and illustrates its potential to improve the safety and efficiency of civil land, air, and sea transport, as well as emergency and rescue operations.
This Carnegie Mellon University Robotics Institute seminar, by Kim Baraka at Vrije Universiteit Amsterdam, is on the topic “Why We Should Build Robot Apprentices and Why We Shouldn’t Do It Alone.”
For robots to be able to truly integrate human-populated, dynamic, and unpredictable environments, they will have to have strong adaptive capabilities. In this talk, I argue that these adaptive capabilities should leverage interaction with end users, who know how (they want) a robot to act in that environment. I will present an overview of my past and ongoing work on the topic of human-interactive robot learning, a growing interdisciplinary subfield that embraces rich, bidirectional interaction to shape robot learning. I will discuss contributions on the algorithmic, interface, and interaction design fronts, showcasing several collaborations with animal behaviorists/trainers, dancers, puppeteers, and medical practitioners.
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Alex’s actuators are all designed in-house, and the next version will feature new grippers that allow for quicker tool changes.Boardwalk Robotics
Alex is available for researchers to purchase immediately.Boardwalk Robotics
Perceptive’s handheld optical coherence tomography imager scans for tooth decay.Perceptive
Perceptive’s imager can create detailed 3D maps of the insides of teeth.Perceptive
The robot is mechanically coupled to your mouth for movement compensation.Perceptive
The robot is still in the prototype phase but could be available within a few years.Perceptive
Perceptive has successfully used its robot on real human patients, as shown in this sped-up footage. In reality the robot moves slightly slower than a human dentist.Perceptive
Elephant Robotics
The dock removes debris from the vacuum, refills it with clean water, and then uses water to wash the mopping pad.iRobot
The Roomba will detect carpet and lift its mopping pad up to prevent drips.iRobot
The robot autonomously switches mopping mode on and off for different floor surfaces.iRobot
The dock opens from the front for access to the clean- and dirty-water storage and the dirt bag.iRobot
VERO has been tested successfully in six different scenarios that challenge both its locomotion and detection capabilities.IIT
Nic Radford
Jerry Pratt
