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#438606 Hyundai Motor Group Introduces Two New ...

Over the past few weeks, we’ve seen a couple of new robots from Hyundai Motor Group. This is a couple more robots than I think I’ve seen from Hyundai Motor Group, like, ever. We’re particularly interested in them right now mostly because Hyundai Motor Group are the new owners of Boston Dynamics, and so far, these robots represent one of the most explicit indications we’ve got about exactly what Hyundai Motor Group wants their robots to be doing.

We know it would be a mistake to read too much into these new announcements, but we can’t help reading something into them, right? So let’s take a look at what Hyundai Motor Group has been up to recently. This first robot is DAL-e, what HMG is calling an “Advanced Humanoid Robot.”

According to Hyundai, DAL-e is “designed to pioneer the future of automated customer services,” and is equipped with “state-of-the-art artificial intelligence technology for facial recognition as well as an automatic communication system based on a language-comprehension platform.” You’ll find it in car showrooms, but only in Seoul, for now.

We don’t normally write about robots like these because they tend not to represent much that’s especially new or interesting in terms of robotic technology, capabilities, or commercial potential. There’s certainly nothing wrong with DAL-e—it’s moderately cute and appears to be moderately functional. We’ve seen other platforms (like Pepper) take on similar roles, and our impression is that the long-term cost effectiveness of these greeter robots tends to be somewhat limited. And unless there’s some hidden functionality that we’re not aware of, this robot doesn’t really seem to be pushing the envelope, but we’d love to be wrong about that.

The other new robot, announced yesterday, is TIGER (Transforming Intelligent Ground Excursion Robot). It’s a bit more interesting, although you’ll have to skip ahead about 1:30 in the video to get to it.

We’ve talked about how adding wheels can make legged robots faster and more efficient, but I’m honestly not sure that it works all that well going the other way (adding legs to wheeled robots) because rather than adding a little complexity to get a multi-modal system that you can use much of the time, you’re instead adding a lot of complexity to get a multi-modal system that you’re going to use sometimes.

You could argue, as perhaps Hyundai would, that the multi-modal system is critical to get TIGER to do what they want it to do, which seems to be primarily remote delivery. They mention operating in urban areas as well, where TIGER could use its legs to climb stairs, but I think it would be beat by more traditional wheeled platforms, or even whegged platforms, that are almost as capable while being much simpler and cheaper. For remote delivery, though, legs might be a necessary feature.

That is, if you assume that using a ground-based system is really the best way to go.

The TIGER concept can be integrated with a drone to transport it from place to place, so why not just use the drone to make the remote delivery instead? I guess maybe if you’re dealing with a thick tree canopy, the drone could drop TIGER off in a clearing and the robot could drive to its destination, but now we’re talking about developing a very complex system for a very specific use case. Even though Hyundai has said that they’re going to attempt to commercialize TIGER over the next five years, I think it’ll be tricky for them to successfully do so.

The best part about these robots from Hyundai is that between the two of them, they suggest that the company is serious about developing commercial robots as well as willing to invest in something that seems a little crazy. And you know who else is both of those things? Boston Dynamics. To be clear, it’s almost certain that both of Hyundai’s robots were developed well before the company was even thinking about acquiring Boston Dynamics, so the real question is: Where do these two companies go from here? Continue reading

Posted in Human Robots

#437091 India’s half-sized space humanoid

On January 23, 2020, the Indian Space Research Organisation (ISRO) introduced Vyommitra, a female half-humanoid (only a torso, no legs). She is able to perform switch panel operations, environment control and life support system functions, and is able to recognize … Continue reading

Posted in Human Robots

#438553 New Drone Software Handles Motor ...

Good as some drones are becoming at obstacle avoidance, accidents do still happen. And as far as robots go, drones are very much on the fragile side of things. Any sort of significant contact between a drone and almost anything else usually results in a catastrophic, out-of-control spin followed by a death plunge to the ground. Bad times. Bad, expensive times.

A few years ago, we saw some interesting research into software that can keep the most common drone form factor, the quadrotor, aloft and controllable even after the failure of one motor. The big caveat to that software was that it relied on GPS for state estimation, meaning that without a GPS signal, the drone is unable to get the information it needs to keep itself under control. In a paper recently accepted to RA-L, researchers at the University of Zurich report that they have developed a vision-based system that brings state estimation completely on-board. The upshot: potentially any drone with some software and a camera can keep itself safe even under the most challenging conditions.

A few years ago, we wrote about first author Sihao Sun’s work on high speed controlled flight of a quadrotor with a non-functional motor. But that innovation relied on an external motion capture system. Since then, Sun has moved from Tu Delft to Davide Scaramuzza’s lab at UZH, and it looks like he’s been able to combine his work on controlled spinning flight with the Robotics and Perception Group’s expertise in vision. Now, a downward-facing camera is all it takes for a spinning drone to remain stable and controllable:

Remember, this software isn’t just about guarding against motor failure. Drone motors themselves don’t just up and fail all that often, either with respect to their software or hardware. But they do represent the most likely point of failure for any drone, usually because when you run into something, what ultimately causes your drone to crash is damage to a motor or a propeller that causes loss of control.

The reason that earlier solutions relied on GPS was because the spinning drone needs a method of state estimation—that is, in order to be closed-loop controllable, the drone needs to have a reasonable understanding of what its position is and how that position is changing over time. GPS is an easy way to take care of this, but GPS is also an external system that doesn’t work everywhere. Having a state estimation system that’s completely internal to the drone itself is much more fail safe, and Sun got his onboard system to work through visual feature tracking with a downward-facing camera, even as the drone is spinning at over 20 rad/s.

While the system works well enough with a regular downward-facing camera—something that many consumer drones are equipped with for stabilization purposes—replacing it with an event camera (you remember event cameras, right?) makes the performance even better, especially in low light.

For more details on this, including what you’re supposed to do with a rapidly spinning partially disabled quadrotor (as well as what it’ll take to make this a standard feature on consumer hardware), we spoke with Sihao Sun via email.

IEEE Spectrum: what usually happens when a drone spinning this fast lands? Is there any way to do it safely?

Sihao Sun: Our experience shows that we can safely land the drone while it is spinning. When the range sensor measurements are lower than a threshold (around 10 cm, indicating that the drone is close to the ground), we switch off the rotors. During the landing procedure, despite the fast spinning motion, the thrust direction oscillates around the gravity vector, thus the drone touches the ground with its legs without damaging other components.

Can your system handle more than one motor failure?

Yes, the system can also handle the failure of two opposing rotors. However, if two adjacent rotors or more than two rotors fail, our method cannot save the quadrotor. Some research has shown that it is possible to control a quadrotor with only one remaining rotor. But the drone requires a very special inertial property, which is hard to satisfy in real applications.

How different is your system's performance from a similar system that relies on GPS, in a favorable environment?

In a favorable environment, our system outperforms those relying on GPS signals because it obtains better position estimates. Since a damaged quadrotor spins fast, the accelerometer readings are largely affected by centrifugal forces. When the GPS signal is lost or degraded, a drone relying on GPS needs to integrate these biased accelerometer measurements for position estimation, leading to large position estimation errors. Feeding these erroneous estimates to the flight controller can easily crash the drone.

When you say that your solution requires “only onboard sensors and computation,” are those requirements specialized, or would they be generally compatible with the current generation of recreational and commercial quadrotors?

We use an NVIDIA Jetson TX2 to run our solution, which includes two parts: the control algorithm and the vision-based state estimation algorithm. The control algorithm is lightweight; thus, we believe that it is compatible with the current generation of quadrotors. On the other hand, the vision-based state estimation requires relatively more computational resources, which may not be affordable for cheap recreational platforms. But this is not an issue for commercial quadrotors because many of them have more powerful processors than a TX2.

What else can event cameras be used for, in recreational or commercial applications?

Many drone applications can benefit from event cameras, especially those in high-speed or low-light conditions, such as autonomous drone racing, cave exploration, drone delivery during night time, etc. Event cameras also consume very little power, which is a significant advantage for energy-critical missions, such as planetary aerial vehicles for Mars explorations. Regarding space applications, we are currently collaborating with JPL to explore the use of event cameras to address the key limitations of standard cameras for the next Mars helicopter.

[ UZH RPG ] Continue reading

Posted in Human Robots

#438294 Video Friday: New Entertainment Robot ...

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.

Engineered Arts' latest Mesmer entertainment robot is Cleo. It sings, gesticulates, and even does impressions.

[ Engineered Arts ]

I do not know what this thing is or what it's saying but Panasonic is going to be selling them and I will pay WHATEVER. IT. COSTS.

Slightly worrisome is that Google Translate persistently thinks that part of the description involves “sleeping and flatulence.”

[ Panasonic ] via [ RobotStart ]

Spot Enterprise is here to help you safely ignore every alarm that goes off at work while you're snug at home in your jammies drinking cocoa.

That Spot needs a bath.

If you missed the launch event (with more on the arm), check it out here:

[ Boston Dynamics ]

PHASA-35, a 35m wingspan solar-electric aircraft successfully completed its maiden flight in Australia, February 2020. Designed to operate unmanned in the stratosphere, above the weather and conventional air traffic, PHASA-35 offers a persistent and affordable alternative to satellites combined with the flexibility of an aircraft, which could be used for a range of valuable applications including forest fire detection and maritime surveillance.

[ BAE Systems ]

As part of the Army Research Lab’s (ARL) Robotics Collaborative Technology Alliance (RCTA), we are developing new planning and control algorithms for quadrupedal robots. The goal of our project is to equip the robot LLAMA, developed by NASA JPL, with the skills it needs to move at operational tempo over difficult terrain to keep up with a human squad. This requires innovative perception, planning, and control techniques to make the robot both precise in execution for navigating technical obstacles and robust enough to reject disturbances and recover from unknown errors.

[ IHMC ]

Watch what happens to this drone when it tries to install a bird diverter on a high voltage power line:

[ GRVC ]

Soldiers navigate a wide variety of terrains to successfully complete their missions. As human/agent teaming and artificial intelligence advance, the same flexibility will be required of robots to maneuver across diverse terrain and become effective combat teammates.

[ Army ]

The goal of the GRIFFIN project is to create something similar to sort of robotic bird, which almost certainly won't look like this concept rendering.

While I think this research is great, at what point is it in fact easier to just, you know, train an actual bird?


Paul Newman narrates this video from two decades ago, which is a pretty neat trick.

[ Oxford Robotics Institute ]

The first step towards a LEGO-based robotic McMuffin creator is cracking and separating eggs.

[ Astonishing Studios ] via [ BB ]

Some interesting soft robotics projects at the University of Southern Denmark.

[ SDU ]

Chong Liu introduces Creature_02, his final presentation for Hod Lipson's Robotics Studio course at Columbia.

[ Chong Liu ]

The world needs more robot blimps.

[ Lab INIT Robots ]

Finishing its duty early, the KR CYBERTECH nano uses this time to play basketball.

[ Kuka ]

senseFly has a new aerial surveying drone that they call “affordable,” although they don't say what the price is.

[ senseFly ]

In summer 2020 participated several science teams of the ETH Zurich at the “Art Safiental” in the mountains of Graubunden. After the scientists packed their hiking gear and their robots, their only mission was “over hill and dale to the summit”. How difficult will it be to reach the summit with a legged robot and an exosceletton? What's the relation of synesthetic dance and robotic? How will the hikers react to these projects?

[ Rienerschnitzel Films ]

Thanks Robert!

Karen Liu: How robots perceive the physical world. A specialist in computer animation expounds upon her rapidly evolving specialty, known as physics-based simulation, and how it is helping robots become more physically aware of the world around them.

[ Stanford ]

This week's UPenn GRASP On Robotics seminar is by Maria Chiara Carrozza from Scuola Superiore Sant’Anna, on “Biorobotics for Personal Assistance – Translational Research and Opportunities for Human-Centered Developments.”

The seminar will focus on the opportunities and challenges offered by the digital transformation of healthcare which was accelerated in the COVID-19 Pandemia. In this framework rehabilitation and social robotics can play a fundamental role as enabling technologies for providing innovative therapies and services to patients even at home or in remote environments.

[ UPenn ] Continue reading

Posted in Human Robots

#438080 Boston Dynamics’ Spot Robot Is Now ...

Boston Dynamics has been working on an arm for its Spot quadruped for at least five years now. There have been plenty of teasers along the way, including this 45-second clip from early 2018 of Spot using its arm to open a door, which at 85 million views seems to be Boston Dynamics’ most popular video ever by a huge margin. Obviously, there’s a substantial amount of interest in turning Spot from a highly dynamic but mostly passive sensor platform into a mobile manipulator that can interact with its environment.

As anyone who’s done mobile manipulation will tell you, actually building an arm is just the first step—the really tricky part is getting that arm to do exactly what you want it to do. In particular, Spot’s arm needs to be able to interact with the world with some amount of autonomy in order to be commercially useful, because you can’t expect a human (remote or otherwise) to spend all their time positioning individual joints or whatever to pick something up. So the real question about this arm is whether Boston Dynamics has managed to get it to a point where it’s autonomous enough that users with relatively little robotics experience will be able to get it to do useful tasks without driving themselves nuts.

Today, Boston Dynamics is announcing commercial availability of the Spot arm, along with some improved software called Scout plus a self-charging dock that’ll give the robot even more independence. And to figure out exactly what Spot’s new arm can do, we spoke with Zachary Jackowski, Spot Chief Engineer at Boston Dynamics.

Although Boston Dynamics’ focus has been on dynamic mobility and legged robots, the company has been working on manipulation for a very long time. We first saw an arm prototype on an early iteration of Spot in 2016, where it demonstrated some impressive functionality, including loading a dishwasher and fetching a beer in a way that only resulted in a minor catastrophe. But we’re guessing that Spot’s arm can trace its history back to BigDog’s crazy powerful hydraulic face-arm, which was causing mayhem with cinder blocks back in 2013:

Spot’s arm is not quite that powerful (it has to drag cinder blocks along the ground rather than fling them into space), but you can certainly see the resemblance. Here’s the video that Boston Dynamics posted yesterday to introduce Spot’s new arm:

A couple of things jumped out from this video right away. First, Spot is doing whole body manipulation with its arm, as opposed to just acting as a four-legged base that brings the arm where it needs to go. Planning looks to be very tightly integrated, such that if you ask the robot to manipulate an object, its arm, legs, and torso all work together to optimize that manipulation. Also, when Spot flips that electrical switch, you see the robot successfully grasp the switch, and then reposition its body in a way that looks like it provides better leverage for the flip, which is a neat trick. It looks like it may be able to use the strength of its legs to augment the strength of its arm, as when it’s dragging the cinder block around, which is surely an homage to BigDog. The digging of a hole is particularly impressive. But again, the real question is how much of this is autonomous or semi-autonomous in a way that will be commercially useful?

Before we get to our interview with Spot Chief Engineer Zack Jackowski, it’s worth watching one more video that Boston Dynamics shared with us:

This is notable because Spot is opening a door that’s not ADA compliant, and the robot is doing it with a simple two-finger gripper. Most robots you see interacting with doors rely on ADA compliant hardware, meaning (among other things) a handle that can be pushed rather than a knob that has to be twisted, because it’s much more challenging for a robot to grasp and twist a smooth round door knob than it is to just kinda bash down on a handle. That capability, combined with Spot being able to pass through a spring-loaded door, potentially opens up a much wider array of human environments to the robot, and that’s where we started our conversation with Jackowski.

IEEE Spectrum: At what point did you decide that for Spot’s arm to be useful, it had to be able to handle round door knobs?

Zachary Jackowski: We're like a lot of roboticists, where someone in a meeting about manipulation would say “it's time for the round doorknob” and people would start groaning a little bit. But the reality is that, in order to make a robot useful, you have to engage with the environments that users have. Spot’s arm uses a very simple gripper—it’s a one degree of freedom gripper, but a ton of thought has gone into all of the fine geometric contours of it such that it can grab that ADA compliant lever handle, and it’ll also do an enclosing grasp around a round door knob. The major point of a robot like Spot is to engage with the environment you have, and so you can’t cut out stuff like round door knobs.

We're thrilled to be launching the arm and getting it out with users and to have them start telling us what doors it works really well on, and what they're having trouble with. And we're going to be working on rapidly improving all this stuff. We went through a few campaigns of like, “this isn’t ready until we can open every single door at Boston Dynamics!” But every single door at Boston Dynamics and at our test lab is a small fraction of all the doors in the world. So we're prepared to learn a lot this year.

When we see Spot open a door, or when it does those other manipulation behaviors in the launch video, how much of that is autonomous, how much is scripted, and to what extent is there a human in the loop?

All of the scenes where the robot does a pick, like the snow scene or the laundry scene, that is actually an almost fully integrated autonomous behavior that has a bit of a script wrapped around it. We trained a detector for an object, and the robot is identifying that object in the environment, picking it, and putting it in the bin all autonomously. The scripted part of that is telling the robot to perform a series of picks.

One of the things that we’re excited about, and that roboticists have been excited about going back probably all the way to the DRC, is semi-autonomous manipulation. And so we have modes built into the interface where if you see an object that you want the robot to grab, all you have to do is tap that object on the screen, and the robot will walk up to it, use the depth camera in its gripper to capture a depth map, and plan a grasp on its own in real time. That’s all built-in, too.

The jump rope—robots don’t just go and jump rope on their own. We scripted an arm motion to move the rope, and wrote a script using our API to coordinate all three robots. Drawing “Boston Dynamics” in chalk in our parking lot was scripted also. One of our engineers wrote a really cool G-code interpreter that vectorizes graphics so that Spot can draw them.

So for an end user, if you wanted Spot to autonomously flip some switches for you, you’d just have to train Spot on your switches, and then Spot could autonomously perform the task?

There are a couple of ways that task could break down depending on how you’re interfacing with the robot. If you’re a tablet user, you’d probably just identify the switch yourself on the tablet’s screen, and the robot will figure out the grasp, and grasp it. Then you’ll enter a constrained manipulation mode on the tablet, and the robot will be able to actuate the switch. But the robot will take care of the complicated controls aspects, like figuring out how hard it has to pull, the center of rotation of the switch, and so on.

The video of Spot digging was pretty cool—how did that work?

That’s mostly a scripted behavior. There are some really interesting control systems topics in there, like how you’d actually do the right kinds of force control while you insert the trowel into the dirt, and how to maintain robot stability while you do it. The higher level task of how to make a good hole in the dirt—that’s scripted. But the part of the problem that’s actually digging, you need the right control system to actually do that, or you’ll dig your trowel into the ground and flip your robot over.

The last time we saw Boston Dynamics robots flipping switches and turning valves I think might have been during the DRC in 2015, when they had expert robot operators with control over every degree of freedom. How are things different now with Spot, and will non-experts in the commercial space really be able to get the robot to do useful tasks?

A lot of the things, like “pick the stuff up in the room,” or ‘turn that switch,” can all be done by a lightly trained operator using just the tablet interface. If you want to actually command all of Spot’s arm degrees of freedom, you can do that— not through the tablet, but the API does expose all of it. That’s actually a notable difference from the base robot; we’ve never opened up the part of the API that lets you command individual leg degrees of freedom, because we don’t think it’s productive for someone to do that. The arm is a little bit different. There are a lot of smart people working on arm motion planning algorithms, and maybe you want to plan your arm trajectory in a super precise way and then do a DRC-style interface where you click to approve it. You can do all that through the API if you want, but fundamentally, it’s also user friendly. It follows our general API design philosophy of giving you the highest level pieces of the toolbox that will enable you to solve a complex problem that we haven't thought of.

Looking back on it now, it’s really cool to see, after so many years, robots do the stuff that Gill Pratt was excited about kicking off with the DRC. And now it’s just a thing you can buy.

Is Spot’s arm safe?

You should follow the same safety rules that you’d follow when working with Spot normally, and that’s that you shouldn’t get within two meters of the robot when it’s powered on. Spot is not a cobot. You shouldn’t hug it. Fundamentally, the places where the robot is the most valuable are places where people don’t want to be, or shouldn’t be.

We’ve seen how people reacted to earlier videos of Spot using its arm—can you help us set some reasonable expectations for what this means for Spot?

You know, it gets right back to the normal assumptions about our robots that people make that aren’t quite reality. All of this manipulation work we’re doing— the robot’s really acting as a tool. Even if it’s an autonomous behavior, it’s a tool. The robot is digging a hole because it’s got a set of instructions that say “apply this much force over this much distance here, here, and here.”

It’s not digging a hole and planting a tree because it loves trees, as much as I’d love to build a robot that works like that.

Photo: Boston Dynamics

There isn’t too much to say about the dock, except that it’s a requirement for making Spot long-term autonomous. The uncomfortable looking charging contacts that Spot impales itself on also include hardwired network connectivity, which is important because Spot often comes back home with a huge amount of data that all needs to be offloaded and processed. Docking and undocking are autonomous— as soon as the robot sees the fiducial markers on the dock, auto docking is enabled and it takes one click to settle the robot down.

During a brief remote demo, we also learned some other interesting things about Spot’s updated remote interface. It’s very latency tolerant, since you don’t have to drive the robot directly (although you can if you want to). Click a point on the camera view and Spot will move there autonomously while avoiding obstacles, meaning that even if you’re dealing with seconds of lag, the robot will continue making safe progress. This will be especially important if (when?) Spot starts exploring the Moon.

The remote interface also has an option to adjust how close Spot can get to obstacles, or to turn the obstacle avoidance off altogether. The latter functionality is useful if Spot sees something as an obstacle that really isn’t, like a curtain, while the former is useful if the robot is operating in an environment where it needs to give an especially wide berth to objects that could be dangerous to run into. “The robot’s not perfect—robots will never be perfect,” Jackowski reminds us, which is something we really (seriously) appreciate hearing from folks working on powerful, dynamic robots. “No matter how good the robot is, you should always de-risk as much as possible.”

Another part of that de-risking is having the user let Spot know when it’s about to go up or down some stairs by putting into “Stair Mode” with a toggle switch in the remote interface. Stairs are still a challenge for Spot, and Stair Mode slows the robot down and encourages it to pitch its body more aggressively to get a better view of the stairs. You’re encouraged to use stair mode, and also encouraged to send Spot up and down stairs with its “head” pointing up the stairs both ways, but these are not requirements for stair navigation— if you want to, you can send Spot down stairs head first without putting it in stair mode. Jackowski says that eventually, Spot will detect stairways by itself even when not in stair mode and adjust itself accordingly, but for now, that de-risking is solidly in the hands of the user.

Spot’s sensor payload, which is what we were trying out for the demo, provided a great opportunity for us to hear Spot STOMP STOMP STOMPING all over the place, which was also an opportunity for us to ask Jackowski why they can’t make Spot a little quieter. “It’s advantageous for Spot to step a little bit hard for the same reason it’s advantageous for you to step a little bit hard if you’re walking around blindfolded—that reason is that it really lets you know where the ground is, particularly when you’re not sure what to expect.” He adds, “It’s all in the name of robustness— the robot might be a little louder, but it’s a little more sure of its footing.”

Boston Dynamics isn’t yet ready to disclose the price of an arm-equipped Spot, but if you’re a potential customer, now is the time to contact the Boston Dynamics sales team to ask them about it. As a reminder, the base model of Spot costs US $74,500, with extra sensing or compute adding a substantial premium on top of that.

There will be a livestream launch event taking place at 11am ET today, during which Boston Dynamics’ CEO Robert Playter, VP of Marketing Michael Perry, and other folks from Boston Dynamics will make presentations on this new stuff. It’ll be live at this link, or you can watch it below. Continue reading

Posted in Human Robots