Tag Archives: flying
#439808 Caltech’s LEO Flying Biped Can ...
Back in February of 2019, we wrote about a sort of humanoid robot thing (?) under development at Caltech, called Leonardo. LEO combines lightweight bipedal legs with torso-mounted thrusters powerful enough to lift the entire robot off the ground, which can handily take care of on-ground dynamic balancing while also enabling some slick aerial maneuvers.
In a paper published today in Science Robotics, the Caltech researchers get us caught up on what they've been doing with LEO for the past several years, and it can now skateboard, slackline, and make dainty airborne hops with exceptionally elegant landings.
Those heels! Seems like a real sponsorship opportunity, right?
The version of LEO you see here is significantly different from the version we first met two years ago. Most importantly, while “Leonardo” used to stand for “LEg ON Aerial Robotic DrOne,” it now stands for “LEgs ONboARD drOne,” which may be the first even moderately successful re-backronym I've ever seen. Otherwise, the robot has been completely redesigned, with the version you see here sharing zero parts in hardware or software with the 2019 version. We're told that the old robot, and I'm quoting from the researchers here, “unfortunately never worked,” in the sense that it was much more limited than the new one—the old design had promise, but it couldn't really walk and the thrusters were only useful for jumping augmentation as opposed to sustained flight.
To enable the new LEO to fly, it now has much lighter weight legs driven by lightweight servo motors. The thrusters have been changed from two coaxial propellers to four tilted propellers, enabling attitude control in all directions. And everything is now onboard, including computers, batteries, and a new software stack. I particularly love how LEO lands into a walking gait so gently and elegantly. Professor Soon-Jo Chung from Caltech's Aerospace Robotics and Control Lab explains how they did it:
Creatures that have more than two locomotion modes must learn and master how to properly switch between them. Birds, for instance, undergo a complex yet intriguing behavior at the transitional interface of their two locomotion modes of flying and walking. Similarly, the Leonardo robot uses synchronized control of distributed propeller-based thrusters and leg joints to realize smooth transitions between its flying and walking modes. In particular, the LEO robot follows a smooth flying trajectory up to the landing point prior to landing. The forward landing velocity is then matched to the chosen walking speed, and the walking phase is triggered when one foot touches the ground. After the touchdown, the robot continues to walk by tracking its walking trajectory. A state machine is run on-board LEO to allow for these smooth transitions, which are detected using contact sensors embedded in the foot.
It's very cool how Leo neatly solves some of the most difficult problems with bipedal robotics, including dynamic balancing and traversing large changes in height. And Leo can also do things that no biped (or human) can do, like actually fly short distances. As a multimodal hybrid of a bipedal robot and a drone, though, it's important to note that Leo's design includes some significant compromises as well. The robot has to be very lightweight in order to fly at all, which limits how effective it can be as a biped without using its thrusters for assistance. And because so much of its balancing requires active input from the thrusters, it's very inefficient relative to both drones and other bipedal robots.
When walking on the ground, LEO (which weighs 2.5kg and is 75cm tall) sucks down 544 watts, of which 445 watts go to the propellers and 99 watts are used by the electronics and legs. When flying, LEO's power consumption almost doubles, but it's obviously much faster—the robot has a cost of transport (a measure of efficiency of self-movement) of 108 when walking at a speed of 20 cm/s, dropping to 15.5 when flying at 3 m/s. Compare this to the cost of transport for an average human, which is well under 1, or a typical quadrupedal robot, which is in the low single digits. The most efficient humanoid we've ever seen, SRI's DURUS, has a cost of transport of about 1, whereas the rumor is that the cost of transport for a robot like Atlas is closer to 20.
Long term, this low efficiency could be a problem for LEO, since its battery life is good for only about 100 seconds of flight or 3.5 minutes of walking. But, explains Soon-Jo Chung, efficiency hasn't yet been a priority, and there's more that can potentially be done to improve LEO's performance, although always with some compromises:
The extreme balancing ability of LEO comes at the cost of continuously running propellers, which leads to higher energy consumption than leg-based ground robots. However, this stabilization with propellers allowed the use of low-power leg servo motors and lightweight legs with flexibility, which was a design choice to minimize the overall weight of LEO to improve its flying performance.
There are possible ways to improve the energy efficiency by making different design tradeoffs. For instance, LEO could walk with the reduced support from the propellers by adopting finite feet for better stability or higher power [leg] motors with torque control for joint actuation that would allow for fast and accurate enough foot position tracking to stabilize the walking gait. In such a case, propellers may need to turn on only when the legs fail to maintain stability on the ground without having to run continuously. These solutions would cause a weight increase and lead to a higher energy consumption during flight maneuvers, but they would lower energy consumption during walking. In the case of LEO, we aimed to achieve balanced aerial and ground locomotion capabilities, and we opted for lightweight legs. Achieving efficient walking with lightweight legs similar to LEO's is still an open challenge in the field of bipedal robots, and it remains to be investigated in future work.
A rendering of a future version of LEO with fancy yellow skins
At this point in its development, the Caltech researchers have been focusing primarily on LEO's mobility systems, but they hope to get LEO doing useful stuff out in the world, and that almost certainly means giving the robot autonomy and manipulation capabilities. At the moment, LEO isn't particularly autonomous, in the sense that it follows predefined paths and doesn't decide on its own whether it should be using walking or flying to traverse a given obstacle. But the researchers are already working on ways in which LEO can make these decisions autonomously through vision and machine learning.
As for manipulation, Chung tells us that “a new version of LEO could be appended with lightweight manipulators that have similar linkage design to its legs and servo motors to expand the range of tasks it can perform,” with the goal of “enabling a wide range of robotic missions that are hard to accomplish by the sole use of ground or aerial robots.”
Perhaps the most well-suited applications for LEO would be the ones that involve physical interactions with structures at a high altitude, which are usually dangerous for human workers and could use robotic workers. For instance, high voltage line inspection or monitoring of tall bridges could be good applications for LEO, and LEO has an onboard camera that can be used for such purposes. In such applications, conventional biped robots have difficulties with reaching the site, and standard multi-rotor drones have an issue with stabilization in high disturbance environments. LEO uses the ground contact to its advantage and, compared to a standard multi-rotor, is more resistant to external disturbances such as wind. This would improve the safety of the robot operation in an outdoor environment where LEO can maintain contact with a rigid surface.
It's also tempting to look at LEO's ability to more or less just bypass so many of the challenges in bipedal robotics and think about ways in which it could be useful in places where bipedal robots tend to struggle. But it's important to remember that because of the compromises inherent in its multimodal design, LEO will likely be best suited for very specific tasks that can most directly leverage what it's particularly good at. High voltage line and bridge inspection is a good start, and you can easily imagine other inspection tasks that require stability combined with vertical agility. Hopefully, improvements in efficiency and autonomy will make this possible, although I'm still holding out for what Caltech's Chung originally promised: “the ultimate form of demonstration for us will be to build two of these Leonardo robots and then have them play tennis or badminton.” Continue reading →
Posted in Human Robots
#439686 We’re Getting Closer to Flying ...
A couple of years ago, we wrote about a bipedal robot called Jet-HR1 under development at the Guangdong University of Technology. With little foot-mounted ducted fans, Jet-HR1 could step across very wide gaps by using the thrust created by the fans to futz with its center of gravity. That's cool and all, but let's take the logical (or not!) next step and see what happens when those ducted fans get cranked up as high as they'll go: flying humanoid robot! Sort of!
This is obviously just the first tentative little airborne hop, but by the end of the video, you can see that the stabilization works pretty well. I wouldn't call it completely controllable yet, but it's tangible progress.
Jet-HR2 has 10 degrees of freedom for ground locomotion, plus four ducted fans, two statically mounted on the robot's waist and two mounted inside the feet that can be actuated through ankle movements. Each fan can deliver 5 kg of thrust, for 20 kg total, enough to lift the 17 kg robot. The thrust to weight ratio here is not great, which is where the control challenge is; without a lot of spare oomph, you have to be very careful about how you allocate thrust. But the system that you see in the video is able to effectively suppress diving and spinning, leading to a stable (although not entirely under control) flying most-of-a-humanoid robot.
A word here on practical applications—there aren't a heck of a lot of good reasons to make a humanoid robot in the first place. So why, then, is a flying humanoid robot actually useful? Or does it get a pass because, I mean, c'mon, a flying humanoid robot, right? Here's what the paper says:
Recently, various disaster-response humanoid robots have been invented with unique control theories and other mechanisms to overcome uneven terrain. Traditionally, humanoid robots have overcome these obstacles by stepping and climbing yet these strategies lack efficiency, especially for dangerous environments like insurmountable obstacles and geological faults. For urgent tasks in complex real scenarios, humanoid robots are expected to have dynamic aerial skills, such as high or long jumps, short distance flights, and hovering that exceed the body length several times.
The performance of humanoid robots is still not up to the human level, especially with an increase in mass. On the other hand, even at the human level, robots may appear helpless on loose, collapse prone, or cliff-like terrain. This seems to be a limitation of using purely joint actuators to generate force. In this study, a novel humanoid robot that can fly using a ducted fan propulsion system was developed to explore its potential value for search and rescue in complex environments.Frequent readers of this site may have seen this one coming: robots for disaster relief and search and rescue tend to be the catch-all justifications for weird mobility concepts without immediately obvious applications. But on the other hand, this is actually one of the reasons why making a humanoid might be a good idea, because having robots that can go where humans go can be very helpful. That is, if you can get them to work, which you probably can't, because practical humanoid robots are super duper hard. What's not hard is imagining how a humanoid robot that can fly could be even more useful. Again, there's that whole getting it to actually work thing, but it's not completely crazy to do some of the foundational research to see what might eventually be possible.
Design of a Flying Humanoid Robot Based on Thrust Vector Control, by Yuhang Li, Yuhao Zhou, Junbin Huang, Zijun Wang, Shunjie Zhu, Kairong Wu, Li Zheng, Jiajin Luo, Rui Cao, Yun Zhang, and Zhifeng Huang, from Guangdong University of Technology, is available on arXiv. Continue reading →
Posted in Human Robots
#439342 Why Flying Cars Could Be Here Within the ...
Flying cars are almost a byword for the misplaced optimism of technologists, but recent news suggests their future may be on slightly firmer footing. The industry has seen a major influx of capital and big automakers seem to be piling in.
What actually constitutes a flying car has changed many times over the decades since the cartoon, The Jetsons, introduced the idea to the popular imagination. Today’s incarnation is known more formally as an electric vertical takeoff and landing (eVTOL) aircraft.
As the name suggests, the vehicles run on battery power rather than aviation fuel, and they’re able to take off and land like a helicopter. Designs vary from what are essentially gigantic multi-rotor drones to small fixed-wing aircraft with rotors that can tilt up or down, allowing them to hover or fly horizontally (like an airplane).
Aerospace companies and startups have been working on the idea for a number of years, but recent news suggests it might be coming closer to fruition. Last Monday, major automakers Hyundai and GM said they are developing vehicles of their own and are bullish about the prospects of this new mode of transport.
And the week prior, British flying car maker Vertical Aerospace announced plans to go public in a deal that values the company at $2.2 billion. Vertical Aerospace also said it had received $4 billion worth of preorders, including from American Airlines and Virgin Atlantic.
The deal was the latest installment in a flood of capital into the sector, with competitors Joby Aviation, Archer Aviation, and Lilium all recently announcing deals to go public too. Also joining them is Blade Urban Mobility, which currently operates heliports but plans to accommodate flying cars when they become available.
When exactly that will be is still uncertain, but there seems to be growing consensus that the second half of this decade might be a realistic prospect. Vertical is aiming to start deliveries by 2024. And the other startups, who already have impressive prototypes, are on a similar timeline.
Hyundai’s global chief operating officer, José Muñoz, told attendees at Reuters’ Car of the Future conference that the company is targeting a 2025 rollout of an air taxi service, while GM’s vice president of global innovation, Pamela Fletcher, went with a more cautious 2030 target. They’re not the only automakers getting in on the act, with Toyota, Daimler, and China’s Geely all developing vehicles alone or in partnership with startups.
Regulators also seem to be increasingly open to the idea.
In January, the Federal Aviation Administration (FAA) announced it expects to certify the first eVTOLs later this year and have regulations around their operation in place by 2023. And last month the European Union Aviation Safety Agency said it expected air taxi services to be running by 2024 or 2025.
While it seems fairly settled that the earliest flying cars will be taxis rather than private vehicles, a major outstanding question is the extent to which they will be automated.
The majority of prototypes currently rely on a human to pilot them. But earlier this month Larry Page’s air taxi startup Kitty Hawk announced it would buy drone maker 3D Robotics as it seeks to shift to a fully autonomous setup. The FAA recently created a new committee to draft a regulatory path for beyond-visual-line-of-sight (BVLOS) autonomous drone flights. This would likely be a first step along the path to allowing unmanned passenger aircraft.
What seems more certain is that there will be winners and losers in the recent rush to corner the air mobility market. As Chris Bryant points out in Bloomberg, these companies still face a host of technological, regulatory, and social hurdles, and the huge amounts of money flooding into the sector may be hard to justify.
Regardless of which companies make it out the other side, it’s looking increasingly likely that air taxis will be a significant new player in urban transport by the end of the decade.
Image Credit: Joby Aviation Continue reading →
Posted in Human Robots
#439089 Ingenuity’s Chief Pilot Explains How ...
On April 11, the Mars helicopter Ingenuity will take to the skies of Mars for the first time. It will do so fully autonomously, out of necessity—the time delay between Ingenuity’s pilots at the Jet Propulsion Laboratory and Jezero Crater on Mars makes manual or even supervisory control impossible. So the best that the folks at JPL can do is practice as much as they can in simulation, and then hope that the helicopter can handle everything on its own.
Here on Earth, simulation is a critical tool for many robotics applications, because it doesn’t rely on access to expensive hardware, is non-destructive, and can be run in parallel and at faster-than-real-time speeds to focus on solving specific problems. Once you think you’ve gotten everything figured out in simulation, you can always give it a try on the real robot and see how close you came. If it works in real life, great! And if not, well, you can tweak some stuff in the simulation and try again.
For the Mars helicopter, simulation is much more important, and much higher stakes. Testing the Mars helicopter under conditions matching what it’ll find on Mars is not physically possible on Earth. JPL has flown engineering models in Martian atmospheric conditions, and they’ve used an actuated tether to mimic Mars gravity, but there’s just no way to know what it’ll be like flying on Mars until they’ve actually flown on Mars. With that in mind, the Ingenuity team has been relying heavily on simulation, since that’s one of the best tools they have to prepare for their Martian flights. We talk with Ingenuity’s Chief Pilot, Håvard Grip, to learn how it all works.
Ingenuity Facts:
Body Size: a box of tissues
Brains: Qualcomm Snapdragon 801
Weight: 1.8 kilograms
Propulsion: Two 1.2m carbon fiber rotors
Navigation sensors: VGA camera, laser altimeter, inclinometer
Ingenuity is scheduled to make its first flight no earlier than April 11. Before liftoff, the Ingenuity team will conduct a variety of pre-flight checks, including verifying the responsiveness of the control system and spinning the blades up to full speed (2,537 rpm) without lifting off. If everything looks good, the first flight will consist of a 1 meter per second climb to 3 meters, 30 seconds of hover at 3 meters while rotating in place a bit, and then a descent to landing. If Ingenuity pulls this off, that will have made its entire mission a success. There will be more flights over the next few weeks, but all it takes is one to prove that autonomous helicopter flight on Mars is possible.
Last month, we spoke with Mars Helicopter Operations Lead Tim Canham about Ingenuity’s hardware, software, and autonomy, but we wanted to know more about how the Ingenuity team has been using simulation for everything from vehicle design to flight planning. To answer our questions, we talked with JPL’s Håvard Grip, who led the development of Ingenuity’s navigation and flight control systems. Grip also has the title of Ingenuity Chief Pilot, which is pretty awesome. He summarizes this role as “operating the flight control system to make the helicopter do what we want it to do.”
IEEE Spectrum: Can you tell me about the simulation environment that JPL uses for Ingenuity’s flight planning?
Håvard Grip: We developed a Mars helicopter simulation ourselves at JPL, based on a multi-body simulation framework that’s also developed at JPL, called DARTS/DSHELL. That's a system that has been in development at JPL for about 30 years now, and it's been used in a number of missions. And so we took that multibody simulation framework, and based on it we built our own Mars helicopter simulation, put together our own rotor model, our own aerodynamics models, and everything else that's needed in order to simulate a helicopter. We also had a lot of help from the rotorcraft experts at NASA Ames and NASA Langley.
Image: NASA/JPL
Ingenuity in JPL’s flight simulator.
Without being able to test on Mars, how much validation are you able to do of what you’re seeing in simulation?
We can do a fair amount, but it requires a lot of planning. When we made our first real prototype (with a full-size rotor that looked like what we were thinking of putting on Mars) we first spent a lot of time designing it and using simulation tools to guide that design, and when we were sufficiently confident that we were close enough, and that we understood enough about it, then we actually built the thing and designed a whole suite of tests in a vacuum chamber where where we could replicate Mars atmospheric conditions. And those tests were before we tried to fly the helicopter—they were specifically targeted at what we call system identification, which has to do with figuring out what the true properties, the true dynamics of a system are, compared to what we assumed in our models. So then we got to see how well our models did, and in the places where they needed adjustment, we could go back and do that.
The simulation work that we really started after that very first initial lift test, that’s what allowed us to unlock all of the secrets to building a helicopter that can fly on Mars.
—Håvard Grip, Ingenuity Chief Pilot
We did a lot of this kind of testing. It was a big campaign, in several stages. But there are of course things that you can't fully replicate, and you do depend on simulation to tie things together. For example, we can't truly replicate Martian gravity on Earth. We can replicate the atmosphere, but not the gravity, and so we have to do various things when we fly—either make the helicopter very light, or we have to help it a little bit by pulling up on it with a string to offload some of the weight. These things don't fully replicate what it will be like on Mars. We also can't simultaneously replicate the Mars aerodynamic environment and the physical and visual surroundings that the helicopter will be flying in. These are places where simulation tools definitely come in handy, with the ability to do full flight tests from A to B, with the helicopter taking off from the ground, running the flight software that it will be running on board, simulating the images that the navigation camera takes of the ground below as it flies, feeding that back into the flight software, and then controlling it.
To what extent can simulation really compensate for the kinds of physical testing that you can’t do on Earth?
It gives you a few different possibilities. We can take certain tests on Earth where we replicate key elements of the environment, like the atmosphere or the visual surroundings for example, and you can validate your simulation on those parameters that you can test on Earth. Then, you can combine those things in simulation, which gives you the ability to set up arbitrary scenarios and do lots and lots of tests. We can Monte Carlo things, we can do a flight a thousand times in a row, with small perturbations of various parameters and tease out what our sensitivities are to those things. And those are the kinds of things that you can't do with physical tests, both because you can't fully replicate the environment and also because of the resources that would be required to do the same thing a thousand times in a row.
Because there are limits to the physical testing we can do on Earth, there are elements where we know there's more uncertainty. On those aspects where the uncertainty is high, we tried to build in enough margin that we can handle a range of things. And simulation gives you the ability to then maybe play with those parameters, and put them at their outer limits, and test them beyond where the real parameters are going to be to make sure that you have robustness even in those extreme cases.
How do you make sure you’re not relying on simulation too much, especially since in some ways it’s your only option?
It’s about anchoring it in real data, and we’ve done a lot of that with our physical testing. I think what you’re referring to is making your simulation too perfect, and we’re careful to model the things that matter. For example, the simulated sensors that we use have realistic levels of simulated noise and bias in them, the navigation camera images have realistic levels of degradation, we have realistic disturbances from wind gusts. If you don’t properly account for those things, then you’re missing important details. So, we try to be as accurate as we can, and to capture that by overbounding in areas where we have a high degree of uncertainty.
What kinds of simulated challenges have you put the Mars helicopter through, and how do you decide how far to push those challenges?
One example is that we can simulate going over rougher terrain. We can push that, and see how far we can go and still have the helicopter behave the way that we want it to. Or we can inject levels of noise that maybe the real sensors don't see, but you want to just see how far you can push things and make sure that it's still robust.
Where we put the limits on this and what we consider to be realistic is often a challenge. We consider this on a case by case basis—if you have a sensor that you're dealing with, you try to do testing with it to characterize it and understand its performance as much as possible, and you build a level of confidence in it that allows you to find the proper balance.
When it comes to things like terrain roughness, it's a little bit of a different thing, because we're actually picking where we're flying the helicopter. We have made that choice, and we know what the terrain looks like around us, so we don’t have to wonder about that anymore.
Image: NASA/JPL-Caltech/University of Arizona
Satellite image of the Ingenuity flight area.
The way that we’re trying to approach this operationally is that we should be done with the engineering at this point. We’re not depending on going back and resimulating things, other than a few checks here and there.
Are there any examples of things you learned as part of the simulation process that resulted in changes to the hardware or mission?
You know, it’s been a journey. One of the early things that we discovered as part of modeling the helicopter was that the rotor dynamics were quite different for a helicopter on Mars, in particular with respect to how the rotor responds to the up and down bending of the blades because they’re not perfectly rigid. That motion is a very important influence on the overall flight dynamics of the helicopter, and what we discovered as we started modeling was that this motion is damped much less on Mars. Under-damped oscillatory things like that, you kind of figure might pose a control issue, and that is the case here: if you just naively design it as you might a helicopter on Earth, without taking this into account, you could have a system where the response to control inputs becomes very sluggish. So that required changes to the vehicle design from some of the very early concepts, and it led us to make a rotor that’s extremely light and rigid.
The design cycle for the Mars helicopter—it’s not like we could just build something and take it out to the back yard and try it and then come back and tweak it if it doesn’t work. It’s a much bigger effort to build something and develop a test program where you have to use a vacuum chamber to test it. So you really want to get as close as possible up front, on your first iteration, and not have to go back to the drawing board on the basic things.
So how close were you able to get on your first iteration of the helicopter design?
[This video shows] a very early demo which was done more or less just assuming that things were going to behave as they would on Earth, and that we’d be able to fly in a Martian atmosphere just spinning the rotor faster and having a very light helicopter. We were basically just trying to demonstrate that we could produce enough lift. You can see the helicopter hopping around, with someone trying to joystick it, but it turned out to be very hard to control. This was prior to doing any of the modeling that I talked about earlier. But once we started seriously focusing on the modeling and simulation, we then went on to build a prototype vehicle which had a full-size rotor that’s very close to the rotor that will be flying on Mars. One difference is that prototype had cyclic control only on the lower rotor, and later we added cyclic control on the upper rotor as well, and that decision was informed in large part by the work we did in simulation—we’d put in the kinds of disturbances that we thought we might see on Mars, and decided that we needed to have the extra control authority.
How much room do you think there is for improvement in simulation, and how could that help you in the future?
The tools that we have were definitely sufficient for doing the job that we needed to do in terms of building a helicopter that can fly on Mars. But simulation is a compute-intensive thing, and so I think there’s definitely room for higher fidelity simulation if you have the compute power to do so. For a future Mars helicopter, you could get some benefits by more closely coupling together high-fidelity aerodynamic models with larger multi-body models, and doing that in a fast way, where you can iterate quickly. There’s certainly more potential for optimizing things.
Photo: NASA/JPL-Caltech
Ingenuity preparing for flight.
Watching Ingenuity’s first flight take place will likely be much like watching the Perseverance landing—we’ll be able to follow along with the Ingenuity team while they send commands to the helicopter and receive data back, although the time delay will mean that any kind of direct control won’t be possible. If everything goes the way it’s supposed to, there will hopefully be some preliminary telemetry from Ingenuity saying so, but it sounds like we’ll likely have to wait until April 12 before we get pictures or video of the flight itself.
Because Mars doesn’t care what time it is on Earth, the flight will actually be taking place very early on April 12, with the JPL Mission Control livestream starting at 3:30 a.m. EDT (12:30 a.m. PDT). Details are here. Continue reading →
Posted in Human Robots
#439010 Video Friday: Nanotube-Powered Insect ...
Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!):
HRI 2021 – March 8-11, 2021 – [Online Conference]
RoboSoft 2021 – April 12-16, 2021 – [Online Conference]
ICRA 2021 – May 30-5, 2021 – Xi'an, China
Let us know if you have suggestions for next week, and enjoy today's videos.
If you’ve ever swatted a mosquito away from your face, only to have it return again (and again and again), you know that insects can be remarkably acrobatic and resilient in flight. Those traits help them navigate the aerial world, with all of its wind gusts, obstacles, and general uncertainty. Such traits are also hard to build into flying robots, but MIT Assistant Professor Kevin Yufeng Chen has built a system that approaches insects’ agility.
Chen’s actuators can flap nearly 500 times per second, giving the drone insect-like resilience. “You can hit it when it’s flying, and it can recover,” says Chen. “It can also do aggressive maneuvers like somersaults in the air.” And it weighs in at just 0.6 grams, approximately the mass of a large bumble bee. The drone looks a bit like a tiny cassette tape with wings, though Chen is working on a new prototype shaped like a dragonfly.
[ MIT ]
National Robotics Week is April 3-11, 2021!
[ NRW ]
This is in a motion capture environment, but still, super impressive!
[ Paper ]
Thanks Fan!
Why wait for Boston Dynamics to add an arm to your Spot if you can just do it yourself?
[ ETHZ ]
This video shows the deep-sea free swimming of soft robot in the South China Sea. The soft robot was grasped by a robotic arm on ‘HAIMA’ ROV and reached the bottom of the South China Sea (depth of 3,224 m). After the releasing, the soft robot was actuated with an on-board AC voltage of 8 kV at 1 Hz and demonstrated free swimming locomotion with its flapping fins.
Um, did they bring it back?
[ Nature ]
Quadruped Yuki Mini is 12 DOF robot equipped with a Raspberry Pi that runs ROS. Also, BUNNIES!
[ Lingkang Zhang ]
Thanks Lingkang!
Deployment of drone swarms usually relies on inter-agent communication or visual markers that are mounted on the vehicles to simplify their mutual detection. The vswarm package enables decentralized vision-based control of drone swarms without relying on inter-agent communication or visual fiducial markers. The results show that the drones can safely navigate in an outdoor environment despite substantial background clutter and difficult lighting conditions.
[ Vswarm ]
A conventional adopted method for operating a waiter robot is based on the static position control, where pre-defined goal positions are marked on a map. However, this solution is not optimal in a dynamic setting, such as in a coffee shop or an outdoor catering event, because the customers often change their positions. We explore an alternative human-robot interface design where a human operator communicates the identity of the customer to the robot instead. Inspired by how [a] human communicates, we propose a framework for communicating a visual goal to the robot, through interactive two-way communications.
[ Paper ]
Thanks Poramate!
In this video, LOLA reacts to undetected ground height changes, including a drop and leg-in-hole experiment. Further tests show the robustness to vertical disturbances using a seesaw. The robot is technically blind, not using any camera-based or prior information on the terrain.
[ TUM ]
RaiSim is a cross-platform multi-body physics engine for robotics and AI. It fully supports Linux, Mac OS, and Windows.
[ RaiSim ]
Thanks Fan!
The next generation of LoCoBot is here. The LoCoBot is an ROS research rover for mapping, navigation and manipulation (optional) that enables researchers, educators and students alike to focus on high level code development instead of hardware and building out lower level code. Development on the LoCoBot is simplified with open source software, full ROS-mapping and navigation packages and modular opensource Python API that allows users to move the platform as well as (optional) manipulator in as few as 10 lines of code.
[ Trossen ]
MIT Media Lab Research Specialist Dr. Kate Darling looks at how robots are portrayed in popular film and TV shows.
Kate's book, The New Breed: What Our History with Animals Reveals about Our Future with Robots can be pre-ordered now and comes out next month.
[ Kate Darling ]
The current autonomous mobility systems for planetary exploration are wheeled rovers, limited to flat, gently-sloping terrains and agglomerate regolith. These vehicles cannot tolerate instability and operate within a low-risk envelope (i.e., low-incline driving to avoid toppling). Here, we present ‘Mars Dogs’ (MD), four-legged robotic dogs, the next evolution of extreme planetary exploration.
[ Team CoSTAR ]
In 2020, first-year PhD students at the MIT Media Lab were tasked with a special project—to reimagine the Lab and write sci-fi stories about the MIT Media Lab in the year 2050. “But, we are researchers. We don't only write fiction, we also do science! So, we did what scientists do! We used a secret time machine under the MIT dome to go to the year 2050 and see what’s going on there! Luckily, the Media Lab still exists and we met someone…really cool!” Enjoy this interview of Cyber Joe, AI Mentor for MIT Media Lab Students of 2050.
[ MIT ]
In this talk, we will give an overview of the diverse research we do at CSIRO’s Robotics and Autonomous Systems Group and delve into some specific technologies we have developed including SLAM and Legged robotics. We will also give insights into CSIRO’s participation in the current DARPA Subterranean Challenge where we are deploying a fleet of heterogeneous robots into GPS-denied unknown underground environments.
[ GRASP Seminar ]
Marco Hutter (ETH) and Hae-Won Park (KAIST) talk about “Robotics Inspired by Nature.”
[ Swiss-Korean Science Club ]
Thanks Fan!
In this keynote, Guy Hoffman Assistant Professor and the Mills Family Faculty Fellow in the Sibley School of Mechanical and Aerospace Engineering at Cornell University, discusses “The Social Uncanny of Robotic Companions.”
[ Designerly HRI ] Continue reading →
Posted in Human Robots