Tag Archives: urban
#437667 17 Teams to Take Part in DARPA’s ...
Among all of the other in-person events that have been totally wrecked by COVID-19 is the Cave Circuit of the DARPA Subterranean Challenge. DARPA has already hosted the in-person events for the Tunnel and Urban SubT circuits (see our previous coverage here), and the plan had always been for a trio of events representing three uniquely different underground environments in advance of the SubT Finals, which will somehow combine everything into one bonkers course.
While the SubT Urban Circuit event snuck in just under the lockdown wire in late February, DARPA made the difficult (but prudent) decision to cancel the in-person Cave Circuit event. What this means is that there will be no Systems Track Cave competition, which is a serious disappointment—we were very much looking forward to watching teams of robots navigating through an entirely unpredictable natural environment with a lot of verticality. Fortunately, DARPA is still running a Virtual Cave Circuit, and 17 teams will be taking part in this competition featuring a simulated cave environment that’s as dynamic and detailed as DARPA can make it.
From DARPA’s press releases:
DARPA’s Subterranean (SubT) Challenge will host its Cave Circuit Virtual Competition, which focuses on innovative solutions to map, navigate, and search complex, simulated cave environments November 17. Qualified teams have until Oct. 15 to develop and submit software-based solutions for the Cave Circuit via the SubT Virtual Portal, where their technologies will face unknown cave environments in the cloud-based SubT Simulator. Until then, teams can refine their roster of selected virtual robot models, choose sensor payloads, and continue to test autonomy approaches to maximize their score.
The Cave Circuit also introduces new simulation capabilities, including digital twins of Systems Competition robots to choose from, marsupial-style platforms combining air and ground robots, and breadcrumb nodes that can be dropped by robots to serve as communications relays. Each robot configuration has an associated cost, measured in SubT Credits – an in-simulation currency – based on performance characteristics such as speed, mobility, sensing, and battery life.
Each team’s simulated robots must navigate realistic caves, with features including natural terrain and dynamic rock falls, while they search for and locate various artifacts on the course within five meters of accuracy to score points during a 60-minute timed run. A correct report is worth one point. Each course contains 20 artifacts, which means each team has the potential for a maximum score of 20 points. Teams can leverage numerous practice worlds and even build their own worlds using the cave tiles found in the SubT Tech Repo to perfect their approach before they submit one official solution for scoring. The DARPA team will then evaluate the solution on a set of hidden competition scenarios.
Of the 17 qualified teams (you can see all of them here), there are a handful that we’ll quickly point out. Team BARCS, from Michigan Tech, was the winner of the SubT Virtual Urban Circuit, meaning that they may be the team to beat on Cave as well, although the course is likely to be unique enough that things will get interesting. Some Systems Track teams to watch include Coordinated Robotics, CTU-CRAS-NORLAB, MARBLE, NUS SEDS, and Robotika, and there are also a handful of brand new teams as well.
Now, just because there’s no dedicated Cave Circuit for the Systems Track teams, it doesn’t mean that there won’t be a Cave component (perhaps even a significant one) in the final event, which as far as we know is still scheduled to happen in fall of next year. We’ve heard that many of the Systems Track teams have been testing out their robots in caves anyway, and as the virtual event gets closer, we’ll be doing a sort of Virtual Systems Track series that highlights how different teams are doing mock Cave Circuits in caves they’ve found for themselves.
For more, we checked in with DARPA SubT program manager Dr. Timothy H. Chung.
IEEE Spectrum: Was it a difficult decision to cancel the Systems Track for Cave?
Tim Chung: The decision to go virtual only was heart wrenching, because I think DARPA’s role is to offer up opportunities that may be unimaginable for some of our competitors, like opening up a cave-type site for this competition. We crawled and climbed through a number of these sites, and I share the sense of disappointment that both our team and the competitors have that we won’t be able to share all the advances that have been made since the Urban Circuit. But what we’ve been able to do is pour a lot of our energy and the insights that we got from crawling around in those caves into what’s going to be a really great opportunity on the Virtual Competition side. And whether it’s a global pandemic, or just lack of access to physical sites like caves, virtual environments are an opportunity that we want to develop.
“The simulator offers us a chance to look at where things could be … it really allows for us to find where some of those limits are in the technology based only on our imagination.”
—Timothy H. Chung, DARPA
What kind of new features will be included in the Virtual Cave Circuit for this competition?
I’m really excited about these particular features because we’re seeing an opportunity for increased synergy between the physical and the virtual. The first I’d say is that we scanned some of the Systems Track robots using photogrammetry and combined that with some additional models that we got from the systems competitors themselves to turn their systems robots into virtual models. We often talk about the sim to real transfer and how successful we can get a simulation to transfer over to the physical world, but now we’ve taken something from the physical world and made it virtual. We’ve validated the controllers as well as the kinematics of the robots, we’ve iterated with the systems competitors themselves, and now we have these 13 robots (air and ground) in the SubT Tech Repo that now all virtual competitors can take advantage of.
We also have additional robot capability. Those comms bread crumbs are common among many of the competitors, so we’ve adopted that in the virtual world, and now you have comms relay nodes that are baked in to the SubT Simulator—you can have either six or twelve comms nodes that you can drop from a variety of our ground robot platforms. We have the marsupial deployment capability now, so now we have parent ground robots that can be mixed and matched with different child drones to become marsupial pairs.
And this is something I’ve been planning for for a while: we now have the ability to trigger things like rock falls. They still don’t quite look like Indiana Jones with the boulder coming down the corridor, but this comes really close. In addition to it just being an interesting and realistic consideration, we get to really dynamically test and stress the robots’ ability to navigate and recognize that something has changed in the environment and respond to it.
Image: DARPA
DARPA is still running a Virtual Cave Circuit, and 17 teams will be taking part in this competition featuring a simulated cave environment.
No simulation is perfect, so can you talk to us about what kinds of things aren’t being simulated right now? Where does the simulator not match up to reality?
I think that question is foundational to any conversation about simulation. I’ll give you a couple of examples:
We have the ability to represent wholesale damage to a robot, but it’s not at the actuator or component level. So there’s not a reliability model, although I think that would be really interesting to incorporate so that you could do assessments on things like mean time to failure. But if a robot falls off a ledge, it can be disabled by virtue of being too damaged to continue.
With communications, and this is one that’s near and dear not only to my heart but also to all of those that have lived through developing communication systems and robotic systems, we’ve gone through and conducted RF surveys of underground environments to get a better handle on what propagation effects are. There’s a lot of research that has gone into this, and trying to carry through some of that realism, we do have path loss models for RF communications baked into the SubT Simulator. For example, when you drop a bread crumb node, it’s using a path loss model so that it can represent the degradation of signal as you go farther into a cave. Now, we’re not modeling it at the Maxwell equations level, which I think would be awesome, but we’re not quite there yet.
We do have things like battery depletion, sensor degradation to the extent that simulators can degrade sensor inputs, and things like that. It’s just amazing how close we can get in some places, and how far away we still are in others, and I think showing where the limits are of how far you can get simulation is all part and parcel of why SubT Challenge wants to have both System and Virtual tracks. Simulation can be an accelerant, but it’s not going to be the panacea for development and innovation, and I think all the competitors are cognizant those limitations.
One of the most amazing things about the SubT Virtual Track is that all of the robots operate fully autonomously, without the human(s) in the loop that the System Track teams have when they compete. Why make the Virtual Track even more challenging in that way?
I think it’s one of the defining, delineating attributes of the Virtual Track. Our continued vision for the simulation side is that the simulator offers us a chance to look at where things could be, and allows for us to explore things like larger scales, or increased complexity, or types of environments that we can’t physically gain access to—it really allows for us to find where some of those limits are in the technology based only on our imagination, and this is one of the intrinsic values of simulation.
But I think finding a way to incorporate human input, or more generally human factors like teleoperation interfaces and the in-situ stress that you might not be able to recreate in the context of a virtual competition provided a good reason for us to delineate the two competitions, with the Virtual Competition really being about the role of fully autonomous or self-sufficient systems going off and doing their solution without human guidance, while also acknowledging that the real world has conditions that would not necessarily be represented by a fully simulated version. Having said that, I think cognitive engineering still has an incredibly important role to play in human robot interaction.
What do we have to look forward to during the Virtual Competition Showcase?
We have a number of additional features and capabilities that we’ve baked into the simulator that will allow for us to derive some additional insights into our competition runs. Those insights might involve things like the performance of one or more robots in a given scenario, or the impact of the environment on different types of robots, and what I can tease is that this will be an opportunity for us to showcase both the technology and also the excitement of the robots competing in the virtual environment. I’m trying not to give too many spoilers, but we’ll have an opportunity to really get into the details.
Check back as we get closer to the 17 November event for more on the DARPA SubT Challenge. Continue reading
Posted in Human Robots
#437643 Video Friday: Matternet Launches Urban ...
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!):
IROS 2020 – October 25-25, 2020 – [Online]
Bay Area Robotics Symposium – November 20, 2020 – [Online]
ACRA 2020 – December 8-10, 2020 – [Online]
Let us know if you have suggestions for next week, and enjoy today's videos.
Sixteen teams chose their roster of virtual robots and sensor payloads, some based on real-life subterranean robots, and submitted autonomy and mapping algorithms that SubT Challenge officials then tested across eight cave courses in the cloud-based SubT Simulator. Their robots traversed the cave environments autonomously, without any input or adjustments from human operators. The Cave Circuit Virtual Competition teams earned points by correctly finding, identifying, and localizing up to 20 artifacts hidden in the cave courses within five-meter accuracy.
[ SubT ]
This year, the KUKA Innovation Award’s international jury of experts received a total of more than 40 ideas. The five finalist teams had time until November to implement their ideas. A KUKA LBR Med lightweight robot – the first robotic component to be certified for integration into a medical device – has been made available to them for this purpose. Beyond this, the teams have received a training for the hardware and coaching from KUKA experts throughout the competition. At virtual.MEDICA from 16-19.11.2020, the finalists presented their concepts to an international audience of experts and to the Innovation Award jury.
The winner of the KUKA Innovation Award 2020, worth 20,000 euros, is Team HIFUSK from the Scuola Superiore Sant'Anna in Italy.
[ KUKA Innovation Award ]
Like everything else the in-person Cybathlon event was cancelled, but the competition itself took place, just a little more distributed than it would have been otherwise.
[ Cybathlon ]
Matternet, developer of the world's leading urban drone logistics platform, today announced the launch of operations at Labor Berlin Charité Vivantes in Germany. The program kicked-off November 17, 2020 with permanent operations expected to take flight next year, creating the first urban BVLOS [Beyond Visual Line of Sight] medical drone delivery network in the European Union. The drone network expects to significantly improve the timeliness and efficiency of Labor Berlin’s diagnostics services by providing an option to avoid roadway delays, which will improve patient experience with potentially life-saving benefits and lower costs.
Routine BVLOS over an urban area? Impressive.
[ Matternet ]
Robots playing diabolo!
Thanks Thilo!
[ OMRON Sinic X]
Anki's tech has been repackaged into this robot that serves butter:
[ Butter Robot ]
Berkshire Grey just announced our Picking With Purpose Program in which we’ve partnered our robotic automation solutions with food rescue organizations City Harvest and The Greater Boston Food Bank to pick, pack, and distribute food to families in need in time for Thanksgiving. Berkshire Grey donated about 40,000 pounds of food, used one of our robotic automation systems to pick and pack that food into meal boxes for families in need, and our team members volunteered to run the system. City Harvest and The Greater Boston Food Bank are distributing the 4,000 meal boxes we produced. This is just the beginning. We are building a sponsorship program to make Picking With Purpose an ongoing initiative.
[ Berkshire Grey ]
Thanks Peter!
We posted a video previously of Cassie learning to skip, but here's a much more detailed look (accompanying an ICRA submission) that includes some very impressive stair descending.
[ DRL ]
From garage inventors to university students and entrepreneurs, NASA is looking for ideas on how to excavate the Moon’s icy regolith, or dirt, and deliver it to a hypothetical processing plant at the lunar South Pole. The NASA Break the Ice Lunar Challenge, a NASA Centennial Challenge, is now open for registration. The competition will take place over two phases and will reward new ideas and approaches for a system architecture capable of excavating and moving icy regolith and water on the lunar surface.
[ NASA ]
Adaptation to various scene configurations and object properties, stability and dexterity in robotic grasping manipulation is far from explored. This work presents an origami-based shape morphing fingertip design to actively tackle the grasping stability and dexterity problems. The proposed fingertip utilizes origami as its skeleton providing degrees of freedom at desired positions and motor-driven four-bar-linkages as its transmission components to achieve a compact size of the fingertip.
[ Paper ]
“If Roboy crashes… you die.”
[ Roboy ]
Traditionally lunar landers, as well as other large space exploration vehicles, are powered by solar arrays or small nuclear reactors. Rovers and small robots, however, are not big enough to carry their own dedicated power supplies and must be tethered to their larger counterparts via electrical cables. Tethering severely restricts mobility, and cables are prone to failure due to lunar dust (regolith) interfering with electrical contact points. Additionally, as robots become smaller and more complex, they are fitted with additional sensors that require more power, further exacerbating the problem. Lastly, solar arrays are not viable for charging during the lunar night. WiBotic is developing rapid charging systems and energy monitoring base stations for lunar robots, including the CubeRover – a shoebox-sized robot designed by Astrobotic – that will operate autonomously and charge wirelessly on the Moon.
[ WiBotic ]
Watching pick and place robots is my therapy.
[ Soft Robotics ]
It's really, really hard to beat liquid fuel for energy storage, as Quaternium demonstrates with their hybrid drone.
[ Quaternium ]
Thanks Gregorio!
State-of-the-art quadrotor simulators have a rigid and highly-specialized structure: either are they really fast, physically accurate, or photo-realistic. In this work, we propose a novel quadrotor simulator: Flightmare.
[ Flightmare ]
Drones that chuck fire-fighting balls into burning buildings, sure!
[ LARICS ]
If you missed ROS World, that's okay, because all of the talks are now online. Here's the opening keynote from Vivian Chu and Diligent robotics, along with a couple fun lightning talks.
[ ROS World 2020 ]
This week's CMU RI Seminar is by Chelsea Finn from Stanford University, on Data Scalability for Robot Learning.
Recent progress in robot learning has demonstrated how robots can acquire complex manipulation skills from perceptual inputs through trial and error, particularly with the use of deep neural networks. Despite these successes, the generalization and versatility of robots across environment conditions, tasks, and objects remains a major challenge. And, unfortunately, our existing algorithms and training set-ups are not prepared to tackle such challenges, which demand large and diverse sets of tasks and experiences. In this talk, I will discuss two central challenges that pertain to data scalability: first, acquiring large datasets of diverse and useful interactions with the world, and second, developing algorithms that can learn from such datasets. Then, I will describe multiple approaches that we might take to rethink our algorithms and data pipelines to serve these goals. This will include algorithms that allow a real robot to explore its environment in a targeted manner with minimal supervision, approaches that can perform robot reinforcement learning with videos of human trial-and-error experience, and visual model-based RL approaches that are not bottlenecked by their capacity to model everything about the world.
[ CMU RI ] Continue reading
Posted in Human Robots