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#435818 Swappable Flying Batteries Keep Drones ...

Battery power is a limiting factor for robots everywhere, but it’s particularly problematic for drones, which have to make an awkward tradeoff between the amount of battery they carry, the amount of other more useful stuff they carry, and how long they can spend in the air. Consumer drones seem to have settled around about a third of their overall mass in battery, resulting in flight times of 20 to 25 minutes at best, before you have to bring the drone back for a battery swap. And if whatever the drone was supposed to be doing depended on it staying in the air, then you’re pretty much out of luck.

When much larger aircraft have this problem, and in particular military aircraft which sometimes need to stay on-station for long periods of time, the solution is mid-air refueling—why send an aircraft all the way back to its fuel source when you can instead bring the fuel source to the aircraft? It’s easier to do this with liquid fuel than it is with batteries, of course, but researchers at UC Berkeley have come up with a clever solution: You just give the batteries wings. Or, in this case, rotors.

The big quadrotor, which weighs 820 grams, is carrying its own 2.2 Ah lithium-polymer battery that by itself gives it a flight time of about 12 minutes. Each little quadrotor weighs 320 g, including its own 0.8 Ah battery plus a 1.5 Ah battery as cargo. The little ones can’t keep themselves aloft for all that long, but that’s okay, because as flying batteries their only job is to go from ground to the big quadrotor and back again.

Photo: UC Berkeley

The flying batteries land on a tray mounted atop the main drone and align their legs with electrical contacts.

How the flying batteries work
As each flying battery approaches the main quadrotor, the smaller quadrotor takes a position about 30 centimeter above a passive docking tray mounted on top of the bigger drone. It then slowly descends to about 3 cm above, waits for its alignment to be just right, and then drops, landing on the tray which helps align its legs with electrical contacts. As soon as a connection is made, the main quadrotor is able to power itself completely from the smaller drone’s battery payload. Each flying battery can power the main quadrotor for about 6 minutes, and then it flies off and a new flying battery takes its place. If everything goes well, the main quadrotor only uses its primary battery during the undocking and docking phases, and in testing, this boosted its flight time from 12 minutes to nearly an hour.

All of this happens in a motion-capture environment, which is a big constraint, and getting this precision(ish) docking maneuver to work outside, or when the primary drone is moving, is something that the researchers would like to figure out. There are potential applications in situations where continuous monitoring by a drone is important—you could argue that switching off two identical drones might be a simpler way of achieving that, but it also requires two (presumably fancy) drones as opposed to just one plus a bunch of relatively simple and inexpensive flying batteries.

“Flying Batteries: In-flight Battery Switching to Increase Multirotor Flight Time,” by Karan P. Jain and Mark W. Mueller from the High Performance Robotics Lab at UC Berkeley, is available on arXiv. Continue reading

Posted in Human Robots

#435784 Amazon Uses 800 Robots to Run This ...

At Amazon’s re:MARS conference in Las Vegas today, who else but Amazon is introducing two new robots designed to make its fulfillment centers even more fulfilling. Xanthus (named after a mythological horse that could very briefly talk but let’s not read too much into that) is a completely redesigned drive unit, one of the robotic mobile bases that carries piles of stuff around for humans to pick from. It has a thinner profile, a third of the parts, costs half as much, and can wear different modules on top to perform a much wider variety of tasks than its predecessor.

Pegasus (named after a mythological horse that could fly but let’s not read too much into that either) is also a mobile robot, but much smaller than Xanthus, designed to help the company quickly and accurately sort individual packages. For Amazon, it’s a completely new large-scale robotic system involving tightly coordinated fleets of robots tossing boxes down chutes, and it’s just as fun to watch as it sounds.

Amazon has 800 Pegasus units already deployed at a sorting facility in the United States, adding to their newly updated total of 200,000 robotic drive units worldwide.

If the Pegasus system looks familiar, it’s because other warehouse automation companies have had something that’s at least superficially very similar up and running for years.

Photo: Amazon

Pegasus is one of Amazon’s new warehouse robots, equipped with a conveyor belt on top and used in the company’s sorting facilities.

But the most interesting announcement that Amazon made, kind of low key and right at the end of their re:MARS talk, is that they’re working on ways of making some of their mobile robots actually collaborative, leveraging some of the technology that they acquired from Boulder, Colo.-based warehouse robotics startup Canvas Technology earlier this year:

“With our recent acquisition of Canvas, we expect to be able to combine this drive platform with AI and autonomous mobility capabilities, and for the first time, allow our robots to move outside of our robotic drive fields, and interact collaboratively with our associates to do a number of mobility tasks,” said Brad Porter, VP of robotics at Amazon.

At the moment, Amazon’s robots are physically separated from humans except for one highly structured station where the human only interacts with the robot in one or two very specific ways. We were told a few months ago that Amazon would like to have mobile robots that are able to move things through the areas of fulfillment centers that have people in them, but that they’re (quite rightly) worried about the safety aspects of having robots and humans work around each other. Other companies are already doing this on a smaller scale, and it means developing a reliable safety system that can handle randomly moving humans, environmental changes, and all kinds of other stuff. It’s much more difficult than having a nice, clean, roped-off area to work in where a wayward human would be an exception rather than just another part of the job.

Photo: Canvas Technology

A robot created by Canvas Technology, a Boulder, Colo.-based warehouse robotics startup acquired by Amazon earlier this year.

It now seems like Canvas has provided the secret sauce that Amazon needed to start implementing this level of autonomy. As for what it’s going to look like, our best guess is that Amazon is going to have to do a little bit more than slap some extra sensors onto Xanthus or Pegasus, if for no other reason than the robots will almost certainly need more ground clearance to let them operate away from the reliably flat floors that they’re accustomed to. We’re expecting to see them performing many of the tasks that companies like Fetch Robotics and OTTO Motors are doing already—moving everything from small boxes to large pallets to keep humans from having to waste time walking.

Of course, this all feeds back into what drives Amazon more than anything else: efficiency. And for better or worse, humans are not uniquely good at moving things from place to place, so it’s no surprise that Amazon wants to automate that, too. The good news is that, at least for now, Amazon still needs humans to babysit all those robots.

[ Amazon ] Continue reading

Posted in Human Robots

#435779 This Robot Ostrich Can Ride Around on ...

Proponents of legged robots say that they make sense because legs are often required to go where humans go. Proponents of wheeled robots say, “Yeah, that’s great but watch how fast and efficient my robot is, compared to yours.” Some robots try and take advantage of wheels and legs with hybrid designs like whegs or wheeled feet, but a simpler and more versatile solution is to do what humans do, and just take advantage of wheels when you need them.

We’ve seen a few experiments with this. The University of Michigan managed to convince Cassie to ride a Segway, with mostly positive (but occasionally quite negative) results. A Segway, and hoverboard-like systems, can provide wheeled mobility for legged robots over flat terrain, but they can’t handle things like stairs, which is kind of the whole point of having a robot with legs anyway.

Image: UC Berkeley

From left, a Segway, a hovercraft, and hovershoes, with complexity in terms of user control increasing from left to right.

At UC Berkeley’s Hybrid Robotics Lab, led by Koushil Sreenath, researchers have taken things a step further. They are teaching their Cassie bipedal robot (called Cassie Cal) to wheel around on a pair of hovershoes. Hovershoes are like hoverboards that have been chopped in half, resulting in a pair of motorized single-wheel skates. You balance on the skates, and control them by leaning forwards and backwards and left and right, which causes each skate to accelerate or decelerate in an attempt to keep itself upright. It’s not easy to get these things to work, even for a human, but by adding a sensor package to Cassie the UC Berkeley researchers have managed to get it to zip around campus fully autonomously.

Remember, Cassie is operating autonomously here—it’s performing vSLAM (with an Intel RealSense) and doing all of its own computation onboard in real time. Watching it jolt across that cracked sidewalk is particularly impressive, especially considering that it only has pitch control over its ankles and can’t roll its feet to maintain maximum contact with the hovershoes. But you can see the advantage that this particular platform offers to a robot like Cassie, including the ability to handle stairs. Stairs in one direction, anyway.

It’s a testament to the robustness of UC Berkeley’s controller that they were willing to let the robot operate untethered and outside, and it sounds like they’re thinking long-term about how legged robots on wheels would be real-world useful:

Our feedback control and autonomous system allow for swift movement through urban environments to aid in everything from food delivery to security and surveillance to search and rescue missions. This work can also help with transportation in large factories and warehouses.

For more details, we spoke with the UC Berkeley students (Shuxiao Chen, Jonathan Rogers, and Bike Zhang) via email.

IEEE Spectrum: How representative of Cassie’s real-world performance is what we see in the video? What happens when things go wrong?

Cassie’s real-world performance is similar to what we see in the video. Cassie can ride the hovershoes successfully all around the campus. Our current controller allows Cassie to robustly ride the hovershoes and rejects various perturbations. At present, one of the failure modes is when the hovershoe rolls to the side—this happens when it goes sideways down a step or encounters a large obstacle on one side of it, causing it to roll over. Under these circumstances, Cassie doesn’t have sufficient control authority (due to the thin narrow feet) to get the hovershoe back on its wheel.

The Hybrid Robotics Lab has been working on robots that walk over challenging terrain—how do wheeled platforms like hovershoes fit in with that?

Surprisingly, this research is related to our prior work on walking on discrete terrain. While locomotion using legs is efficient when traveling over rough and discrete terrain, wheeled locomotion is more efficient when traveling over flat continuous terrain. Enabling legged robots to ride on various micro-mobility platforms will offer multimodal locomotion capabilities, improving the efficiency of locomotion over various terrains.

Our current research furthers the locomotion ability for bipedal robots over continuous terrains by using a wheeled platform. In the long run, we would like to develop multi-modal locomotion strategies based on our current and prior work to allow legged robots to robustly and efficiently locomote in our daily life.

Photo: UC Berkeley

In their experiments, the UC Berkeley researchers say Cassie proved quite capable of riding the hovershoes over rough and uneven terrain, including going down stairs.

How long did it take to train Cassie to use the hovershoes? Are there any hovershoe skills that Cassie is better at than an average human?

We spent about eight months to develop our whole system, including a controller, a path planner, and a vision system. This involved developing mathematical models of Cassie and the hovershoes, setting up a dynamical simulation, figuring out how to interface and communicate with various sensors and Cassie, and doing several experiments to slowly improve performance. In contrast, a human with a good sense of balance needs a few hours to learn to use the hovershoes. A human who has never used skates or skis will probably need a longer time.

A human can easily turn in place on the hovershoes, while Cassie cannot do this motion currently due to our algorithm requiring a non-zero forward speed in order to turn. However, Cassie is much better at riding the hovershoes over rough and uneven terrain including riding the hovershoes down some stairs!

What would it take to make Cassie faster or more agile on the hovershoes?

While Cassie can currently move at a decent pace on the hovershoes and navigate obstacles, Cassie’s ability to avoid obstacles at rapid speeds is constrained by the sensing, the controller, and the onboard computation. To enable Cassie to dynamically weave around obstacles at high speeds exhibiting agile motions, we need to make progress on different fronts.

We need planners that take into account the entire dynamics of the Cassie-Hovershoe system and rapidly generate dynamically-feasible trajectories; we need controllers that tightly coordinate all the degrees-of-freedom of Cassie to dynamically move while balancing on the hovershoes; we need sensors that are robust to motion-blur artifacts caused due to fast turns; and we need onboard computation that can execute our algorithms at real-time speeds.

What are you working on next?

We are working on enabling more aggressive movements for Cassie on the hovershoes by fully exploiting Cassie’s dynamics. We are working on approaches that enable us to easily go beyond hovershoes to other challenging micro-mobility platforms. We are working on enabling Cassie to step onto and off from wheeled platforms such as hovershoes. We would like to create a future of multi-modal locomotion strategies for legged robots to enable them to efficiently help people in our daily life.

“Feedback Control for Autonomous Riding of Hovershoes by a Cassie Bipedal Robot,” by Shuxiao Chen, Jonathan Rogers, Bike Zhang, and Koushil Sreenath from the Hybrid Robotics Lab at UC Berkeley, has been submitted to IEEE Robotics and Automation Letters with option to be presented at the 2019 IEEE RAS International Conference on Humanoid Robots. Continue reading

Posted in Human Robots

#435757 Robotic Animal Agility

An off-shore wind power platform, somewhere in the North Sea, on a freezing cold night, with howling winds and waves crashing against the impressive structure. An imperturbable ANYmal is quietly conducting its inspection.

ANYmal, a medium sized dog-like quadruped robot, walks down the stairs, lifts a “paw” to open doors or to call the elevator and trots along corridors. Darkness is no problem: it knows the place perfectly, having 3D-mapped it. Its laser sensors keep it informed about its precise path, location and potential obstacles. It conducts its inspection across several rooms. Its cameras zoom in on counters, recording the measurements displayed. Its thermal sensors record the temperature of machines and equipment and its ultrasound microphone checks for potential gas leaks. The robot also inspects lever positions as well as the correct positioning of regulatory fire extinguishers. As the electronic buzz of its engines resumes, it carries on working tirelessly.

After a little over two hours of inspection, the robot returns to its docking station for recharging. It will soon head back out to conduct its next solitary patrol. ANYmal played alongside Mulder and Scully in the “X-Files” TV series*, but it is in no way a Hollywood robot. It genuinely exists and surveillance missions are part of its very near future.

Off-shore oil platforms, the first test fields and probably the first actual application of ANYmal. ©ANYbotics

This quadruped robot was designed by ANYbotics, a spinoff of the Swiss Federal Institute of Technology in Zurich (ETH Zurich). Made of carbon fibre and aluminium, it weighs about thirty kilos. It is fully ruggedised, water- and dust-proof (IP-67). A kevlar belly protects its main body, carrying its powerful brain, batteries, network device, power management system and navigational systems.

ANYmal was designed for all types of terrain, including rubble, sand or snow. It has been field tested on industrial sites and is at ease with new obstacles to overcome (and it can even get up after a fall). Depending on its mission, its batteries last 2 to 4 hours.

On its jointed legs, protected by rubber pads, it can walk (at the speed of human steps), trot, climb, curl upon itself to crawl, carry a load or even jump and dance. It is the need to move on all surfaces that has driven its designers to choose a quadruped. “Biped robots are not easy to stabilise, especially on irregular terrain” explains Dr Péter Fankhauser, co-founder and chief business development officer of ANYbotics. “Wheeled or tracked robots can carry heavy loads, but they are bulky and less agile. Flying drones are highly mobile, but cannot carry load, handle objects or operate in bad weather conditions. We believe that quadrupeds combine the optimal characteristics, both in terms of mobility and versatility.”

What served as a source of inspiration for the team behind the project, the Robotic Systems Lab of the ETH Zurich, is a champion of agility on rugged terrain: the mountain goat. “We are of course still a long way” says Fankhauser. “However, it remains our objective on the longer term.

The first prototype, ALoF, was designed already back in 2009. It was still rather slow, very rigid and clumsy – more of a proof of concept than a robot ready for application. In 2012, StarlETH, fitted with spring joints, could hop, jump and climb. It was with this robot that the team started participating in 2014 in ARGOS, a full-scale challenge, launched by the Total oil group. The idea was to present a robot capable of inspecting an off-shore drilling station autonomously.

Up against dozens of competitors, the ETH Zurich team was the only team to enter the competition with such a quadrupedal robot. They didn’t win, but the multiple field tests were growing evermore convincing. Especially because, during the challenge, the team designed new joints with elastic actuators made in-house. These joints, inspired by tendons and muscles, are compact, sealed and include their own custom control electronics. They can regulate joint torque, position and impedance directly. Thanks to this innovation, the team could enter the same competition with a new version of its robot, ANYmal, fitted with three joints on each leg.

The ARGOS experience confirms the relevance of the selected means of locomotion. “Our robot is lighter, takes up less space on site and it is less noisy” says Fankhauser. “It also overcomes bigger obstacles than larger wheeled or tracked robots!” As ANYmal generated public interest and its transformation into a genuine product seemed more than possible, the startup ANYbotics was launched in 2016. It sold not only its robot, but also its revolutionary joints, called ANYdrive.

Today, ANYmal is not yet ready for sale to companies. However, ANYbotics has a growing number of partnerships with several industries, testing the robot for a few days or several weeks, for all types of tasks. Last October, for example, ANYmal navigated its way through the dark sewage system of the city of Zurich in order to test its capacity to help workers in similar difficult, repetitive and even dangerous tasks.

Why such an early interest among companies? “Because many companies want to integrate robots into their maintenance tasks” answers Fankhauser. “With ANYmal, they can actually evaluate its feasibility and plan their strategy. Eventually, both the architecture and the equipment of buildings could be rethought to be adapted to these maintenance robots”.

ANYmal requires ruggedised, sealed and extremely reliable interconnection solutions, such as LEMO. ©ANYbotics

Through field demonstrations and testing, ANYbotics can gather masses of information (up to 50,000 measurements are recorded every second during each test!) “It helps us to shape the product.” In due time, the startup will be ready to deliver a commercial product which really caters for companies’ needs.

Inspection and surveillance tasks on industrial sites are not the only applications considered. The startup is also thinking of agricultural inspections – with its onboard sensors, ANYmal is capable of mapping its environment, measuring bio mass and even taking soil samples. In the longer term, it could also be used for search and rescue operations. By the way, the robot can already be switched to “remote control” mode at any time and can be easily tele-operated. It is also capable of live audio and video transmission.

The transition from the prototype to the marketed product stage will involve a number of further developments. These include increasing ANYmal’s agility and speed, extending its capacity to map large-scale environments, improving safety, security, user handling and integrating the system with the customer’s data management software. It will also be necessary to enhance the robot’s reliability “so that it can work for days, weeks, or even months without human supervision.” All required certifications will have to be obtained. The locomotion system, which had triggered the whole business, is only one of a number of considerations of ANYbotics.

Designed for extreme environments, for ANYmal smoke is not a problem and it can walk in the snow, through rubble or in water. ©ANYbotics

The startup is not all alone. In fact, it has sold ANYmal robots to a dozen major universities who use them to develop their know-how in robotics. The startup has also founded ANYmal Research, a community including members such as Toyota Research Institute, the German Aerospace Center and the computer company Nvidia. Members have full access to ANYmal’s control software, simulations and documentation. Sharing has boosted both software and hardware ideas and developments (built on ROS, the open-source Robot Operating System). In particular, payload variations, providing for expandability and scalability. For instance, one of the universities uses a robotic arm which enables ANYmal to grasp or handle objects and open doors.

Among possible applications, ANYbotics mentions entertainment. It is not only about playing in more films or TV series, but rather about participating in various attractions (trade shows, museums, etc.). “ANYmal is so novel that it attracts a great amount of interest” confirms Fankhauser with a smile. “Whenever we present it somewhere, people gather around.”

Videos of these events show a fascinated and sometimes slightly fearful audience, when ANYmal gets too close to them. Is it fear of the “bad robot”? “This fear exists indeed and we are happy to be able to use ANYmal also to promote public awareness towards robotics and robots.” Reminiscent of a young dog, ANYmal is truly adapted for the purpose.

However, Péter Fankhauser softens the image of humans and sophisticated robots living together. “These coming years, robots will continue to work in the background, like they have for a long time in factories. Then, they will be used in public places in a selective and targeted way, for instance for dangerous missions. We will need to wait another ten years before animal-like robots, such as ANYmal will share our everyday lives!”

At the Consumer Electronics Show (CES) in Las Vegas in January, Continental, the German automotive manufacturing company, used robots to demonstrate a last-mile delivery. It showed ANYmal getting out of an autonomous vehicle with a parcel, climbing onto the front porch, lifting a paw to ring the doorbell, depositing the parcel before getting back into the vehicle. This futuristic image seems very close indeed.

*X-Files, season 11, episode 7, aired in February 2018 Continue reading

Posted in Human Robots

#435752 T-RHex Is a Hexapod Robot With ...

In Aaron Johnson’s “Robot Design & Experimentation” class at CMU, teams of students have a semester to design and build an experimental robotic system based on a theme. For spring 2019, that theme was “Bioinspired Robotics,” which is definitely one of our favorite kinds of robotics—animals can do all kinds of crazy things, and it’s always a lot of fun watching robots try to match them. They almost never succeed, of course, but even basic imitation can lead to robots with some unique capabilities.

One of the projects from this year’s course, from Team ScienceParrot, is a new version of RHex called T-RHex (pronounced T-Rex, like the dinosaur). T-RHex comes with a tail, but more importantly, it has tiny tapered toes, which help it grip onto rough surfaces like bricks, wood, and concrete. It’s able to climb its way up very steep slopes, and hang from them, relying on its toes to keep itself from falling off.

T-RHex’s toes are called microspines, and we’ve seen them in all kinds of robots. The most famous of these is probably JPL’s LEMUR IIB (which wins on sheer microspine volume), although the concept goes back at least 15 years to Stanford’s SpinyBot. Robots that use microspines to climb tend to be fairly methodical at it, since the microspines have to be engaged and disengaged with care, limiting their non-climbing mobility.

T-RHex manages to perform many of the same sorts of climbing and hanging maneuvers without losing RHex’s ability for quick, efficient wheel-leg (wheg) locomotion.

If you look closely at T-RHex walking in the video, you’ll notice that in its normal forward gait, it’s sort of walking on its ankles, rather than its toes. This means that the microspines aren’t engaged most of the time, so that the robot can use its regular wheg motion to get around. To engage the microspines, the robot moves its whegs backwards, meaning that its tail is arguably coming out of its head. But since all of T-RHex’s capability is mechanical in nature and it has no active sensors, it doesn’t really need a head, so that’s fine.

The highest climbable slope that T-RHex could manage was 55 degrees, meaning that it can’t, yet, conquer vertical walls. The researchers were most surprised by the robot’s ability to cling to surfaces, where it was perfectly happy to hang out on a slope of 135 degrees, which is a 45 degree overhang (!). I have no idea how it would ever reach that kind of position on its own, but it’s nice to know that if it ever does, its spines will keep doing their job.

Photo: CMU

T-RHex uses laser-cut acrylic legs, with the microspines embedded into 3D-printed toes. The tail is needed to prevent the robot from tipping backward.

For more details about the project, we spoke with Team ScienceParrot member (and CMU PhD student) Catherine Pavlov via email.

IEEE Spectrum: We’re used to seeing RHex with compliant, springy legs—how do the new legs affect T-RHex’s mobility?

Catherine Pavlov: There’s some compliance in the legs, though not as much as RHex—this is driven by the use of acrylic, which was chosen for budget/manufacturing reasons. Matching the compliance of RHex with acrylic would have made the tines too weak (since often only a few hold the load of the robot during climbing). It definitely means you can’t use energy storage in the legs the way RHex does, for example when pronking. T-RHex is probably more limited by motor speed in terms of mobility though. We were using some borrowed Dynamixels that didn’t allow for good positioning at high speeds.

How did you design the climbing gait? Why not use the middle legs, and why is the tail necessary?

The gait was a lot of hand-tuning and trial-and-error. We wanted a left/right symmetric gait to enable load sharing among more spines and prevent out-of-plane twisting of the legs. When using all three pairs, you have to have very accurate angular positioning or one leg pair gets pushed off the wall. Since two legs should be able to hold the full robot gait, using the middle legs was hurting more than it was helping, with the middle legs sometimes pushing the rear ones off of the wall.

The tail is needed to prevent the robot from tipping backward and “sitting” on the wall. During static testing we saw the robot tip backward, disengaging the front legs, at around 35 degrees incline. The tail allows us to load the front legs, even when they’re at a shallow angle to the surface. The climbing gait we designed uses the tail to allow the rear legs to fully recirculate without the robot tipping backward.

Photo: CMU

Team ScienceParrot with T-RHex.

What prevents T-RHex from climbing even steeper surfaces?

There are a few limiting factors. One is that the tines of the legs break pretty easily. I think we also need a lighter platform to get fully vertical—we’re going to look at MiniRHex for future work. We’re also not convinced our gait is the best it can be, we can probably get marginal improvements with more tuning, which might be enough.

Can the microspines assist with more dynamic maneuvers?

Dynamic climbing maneuvers? I think that would only be possible on surfaces with very good surface adhesion and very good surface strength, but it’s certainly theoretically possible. The current instance of T-RHex would definitely break if you tried to wall jump though.

What are you working on next?

Our main target is exploring the space of materials for leg fabrication, such as fiberglass, PLA, urethanes, and maybe metallic glass. We think there’s a lot of room for improvement in the leg material and geometry. We’d also like to see MiniRHex equipped with microspines, which will require legs about half the scale of what we built for T-RHex. Longer-term improvements would be the addition of sensors e.g. for wall detection, and a reliable floor-to-wall transition and dynamic gait transitions.

[ T-RHex ] Continue reading

Posted in Human Robots