Tag Archives: tech

#437733 Video Friday: MIT Media Lab Developing ...

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!):

AWS Cloud Robotics Summit – August 18-19, 2020 – [Online Conference]
CLAWAR 2020 – August 24-26, 2020 – [Online Conference]
ICUAS 2020 – September 1-4, 2020 – Athens, Greece
ICRES 2020 – September 28-29, 2020 – Taipei, Taiwan
AUVSI EXPONENTIAL 2020 – October 5-8, 2020 – [Online Conference]
IROS 2020 – October 25-29, 2020 – Las Vegas, Nev., USA
ICSR 2020 – November 14-16, 2020 – Golden, Colo., USA
Let us know if you have suggestions for next week, and enjoy today’s videos.

Very impressive local obstacle avoidance at a fairly high speed on a small drone, both indoors and outdoors.

[ FAST Lab ]

Matt Carney writes:

My PhD at MIT Media Lab has been the design and build of a next generation powered prosthesis. The bionic ankle, named TF8, was designed to provide biologically equivalent power and range of motion for plantarflexion-dorsiflexion. This video shows the process of going from a blank sheet of paper to people walking on it. Shown are three different people wearing the robot. About a dozen people have since been able to test the hardware.

[ MIT ]

Thanks Matt!

Exciting changes are coming to the iRobot® Home App. Get ready for new personalized experiences, improved features, and an easy-to-use interface. The update is rolling out over the next few weeks!

[ iRobot ]

MOFLIN is an AI Pet created from a totally new concept. It possesses emotional capabilities that evolve like living animals. With its warm soft fur, cute sounds, and adorable movement, you’d want to love it forever. We took a nature inspired approach and developed a unique algorithm that allows MOFLIN to learn and grow by constantly using its interactions to determine patterns and evaluate its surroundings from its sensors. MOFLIN will choose from an infinite number of mobile and sound pattern combinations to respond and express its feelings. To put it in simple terms, it’s like you’re interacting with a living pet.

You lost me at “it’s like you’re interacting with a living pet.”

[ Kickstarter ] via [ Gizmodo ]

This video is only robotics-adjacent, but it has applications for robotic insects. With a high-speed tracking system, we can now follow insects as they jump and fly, and watch how clumsy (but effective) they are at it.

[ Paper ]

Thanks Sawyer!

Suzumori Endo Lab, Tokyo Tech has developed self-excited pneumatic actuators that can be integrally molded by a 3D printer. These actuators use the “automatic flow path switching mechanism” we have devised.

[ Suzimori Endo Lab ]

Quadrupeds are getting so much better at deciding where to step rather than just stepping where they like and trying not to fall over.

[ RSL ]

Omnidirectional micro aerial vehicles are a growing field of research, with demonstrated advantages for aerial interaction and uninhibited observation. While systems with complete pose omnidirectionality and high hover efficiency have been developed independently, a robust system that combines the two has not been demonstrated to date. This paper presents the design and optimal control of a novel omnidirectional vehicle that can exert a wrench in any orientation while maintaining efficient flight configurations.

[ ASL ]

The latest in smooth humanoid walking from Dr. Guero.

[ YouTube ]

Will robots replace humans one day? When it comes to space exploration, robots are our precursors, gathering data to prepare humans for deep space. ESA robotics engineer Martin Azkarate discusses some of the upcoming missions involving robots and the unique science they will perform in this episode of Meet the Experts.

[ ESA ]

The Multi-robot Systems Group at FEE-CTU in Prague is working on an autonomous drone that detects fires and the shoots an extinguisher capsule at them.

[ MRS ]

This experiment with HEAP (Hydraulic Excavator for Autonomous Purposes) demonstrates our latest research in on-site and mobile digital fabrication with found materials. The embankment prototype in natural granular material was achieved using state of the art design and construction processes in mapping, modelling, planning and control. The entire process of building the embankment was fully autonomous. An operator was only present in the cabin for safety purposes.

[ RSL ]

The Simulation, Systems Optimization and Robotics Group (SIM) of Technische Universität Darmstadt’s Department of Computer Science conducts research on cooperating autonomous mobile robots, biologically inspired robots and numerical optimization and control methods.

[ SIM ]

Starting January 1, 2021, your drone platform of choice may be severely limited by the European Union’s new drone regulations. In this short video, senseFly’s Brock Ryder explains what that means for drone programs and operators and where senseFly drones fit in the EU’s new regulatory framework.

[ SenseFly ]

Nearly every company across every industry is looking for new ways to minimize human contact, cut costs and address the labor crunch in repetitive and dangerous jobs. WSJ explores why many are looking to robots as the solution for all three.

[ WSJ ]

You’ll need to prepare yourself emotionally for this video on “Examining Users’ Attitude Towards Robot Punishment.”

[ ACM ]

In this episode of the AI Podcast, Lex interviews Russ Tedrake (MIT and TRI) about biped locomotion, the DRC, home robots, and more.

[ AI Podcast ] Continue reading

Posted in Human Robots

#437695 Video Friday: Even Robots Know That You ...

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!):

CLAWAR 2020 – August 24-26, 2020 – [Online Conference]
Other Than Human – September 3-10, 2020 – Stockholm, Sweden
ICRES 2020 – September 28-29, 2020 – Taipei, Taiwan
AUVSI EXPONENTIAL 2020 – October 5-8, 2020 – [Online Conference]
IROS 2020 – October 25-29, 2020 – Las Vegas, Nev., USA
CYBATHLON 2020 – November 13-14, 2020 – [Online Event]
ICSR 2020 – November 14-16, 2020 – Golden, Colo., USA
Let us know if you have suggestions for next week, and enjoy today's videos.

From the Robotics and Perception Group at UZH comes Flightmare, a simulation environment for drones that combines a slick rendering engine with a robust physics engine that can run as fast as your system can handle.

Flightmare is composed of two main components: a configurable rendering engine built on Unity and a flexible physics engine for dynamics simulation. Those two components are totally decoupled and can run independently from each other. Flightmare comes with several desirable features: (i) a large multi-modal sensor suite, including an interface to extract the 3D point-cloud of the scene; (ii) an API for reinforcement learning which can simulate hundreds of quadrotors in parallel; and (iii) an integration with a virtual-reality headset for interaction with the simulated environment. Flightmare can be used for various applications, including path-planning, reinforcement learning, visual-inertial odometry, deep learning, human-robot interaction, etc.

[ Flightmare ]

Quadruped robots yelling at people to maintain social distancing is really starting to become a thing, for better or worse.

We introduce a fully autonomous surveillance robot based on a quadruped platform that can promote social distancing in complex urban environments. Specifically, to achieve autonomy, we mount multiple cameras and a 3D LiDAR on the legged robot. The robot then uses an onboard real-time social distancing detection system to track nearby pedestrian groups. Next, the robot uses a crowd-aware navigation algorithm to move freely in highly dynamic scenarios. The robot finally uses a crowd aware routing algorithm to effectively promote social distancing by using human-friendly verbal cues to send suggestions to overcrowded pedestrians.

[ Project ]

Thanks Fan!

The Personal Robotics Group at Oregon State University is looking at UV germicidal irradiation for surface disinfection with a Fetch Manipulator Robot.

Fetch Robot disinfecting dance party woo!

[ Oregon State ]

How could you not take a mask from this robot?

[ Reachy ]

This work presents the design, development and autonomous navigation of the alpha-version of our Resilient Micro Flyer, a new type of collision-tolerant small aerial robot tailored to traversing and searching within highly confined environments including manhole-sized tubes. The robot is particularly lightweight and agile, while it implements a rigid collision-tolerant design which renders it resilient during forcible interaction with the environment. Furthermore, the design of the system is enhanced through passive flaps ensuring smoother and more compliant collision which was identified to be especially useful in very confined settings.

[ ARL ]

Pepper can make maps and autonomously navigate, which is interesting, but not as interesting as its posture when it's wandering around.

Dat backing into the charging dock tho.

[ Pepper ]

RatChair a strategy for displacing big objects by attaching relatively small vibration sources. After learning how several random bursts of vibration affect its pose, an optimization algorithm discovers the optimal sequence of vibration patterns required to (slowly but surely) move the object to a specified position.

This is from 2015, why isn't all of my furniture autonomous yet?!

[ KAIST ]

The new SeaDrone Pro is designed to be the underwater equivalent of a quadrotor. This video is a rendering, but we've been assured that it does actually exist.

[ SeaDrone ]

Thanks Eduardo!

Porous Loops is a lightweight composite facade panel that shows the potential of 3D printing of mineral foams for building scale applications.

[ ETH ]

Thanks Fan!

Here's an interesting idea for a robotic gripper- it's what appears to be a snap bracelet coupled to a pneumatic actuator that allows the snap bracelet to be reset.

[ Georgia Tech ]

Graze is developing a commercial robotic lawnmower. They're also doing a sort of crowdfunded investment thing, which probably explains the painfully overproduced nature of the following video:

A couple things about this: the hard part, which the video skips over almost entirely, is the mapping, localization, and understanding where to mow and where not to mow. The pitch deck seems to suggest that this is mostly done through computer vision, a thing that's perhaps easy to do under controlled ideal conditions, but difficult to apply to a world full lawns that are all different. The commercial aspect is interesting because golf courses are likely as standardized as you can get, but the emphasis here on how much money they can make without really addressing any of the technical stuff makes me raise an eyebrow or two.

[ Graze ]

The record & playback X-series arm demo allows the user to record the arm's movements while motors are torqued off. Then, the user may torque the motor's on and watch the movements they just made playback!

[ Interbotix ]

Shadow Robot has a new teleop system for its hand. I'm guessing that it's even trickier to use than it looks.

[ Shadow Robot ]

Quanser Interactive Labs is a collection of virtual hardware-based laboratory activities that supplement traditional or online courses. Same as working with physical systems in the lab, students work with virtual twins of Quanser's most popular plants, develop their mathematical models, implement and simulate the dynamic behavior of these systems, design controllers, and validate them on a high-fidelity 3D real-time virtual models. The virtual systems not only look like the real ones, they also behave, can be manipulated, measured, and controlled like real devices. And finally, when students go to the lab, they can deploy their virtually-validated designs on actual physical equipment.

[ Quanser ]

This video shows robot-assisted heart surgery. It's amazing to watch if you haven't seen this sort of thing before, but be aware that there is a lot of blood.

This video demonstrates a fascinating case of robotic left atrial myxoma excision, narrated by Joel Dunning, Middlesbrough, UK. The Robotic platform provides superior visualisation and enhanced dexterity, through keyhole incisions. Robotic surgery is an integral part of our Minimally Invasive Cardiothoracic Surgery Program.

[ Tristan D. Yan ]

Thanks Fan!

In this talk, we present our work on learning control policies directly in simulation that are deployed onto real drones without any fine tuning. The presentation covers autonomous drone racing, drone acrobatics, and uncertainty estimation in deep networks.

[ RPG ] Continue reading

Posted in Human Robots

#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

#437564 How We Won the DARPA SubT Challenge: ...

This is a guest post. The views expressed here are those of the authors and do not necessarily represent positions of IEEE or its organizational units.​

“Do you smell smoke?” It was three days before the qualification deadline for the Virtual Tunnel Circuit of the DARPA Subterranean Challenge Virtual Track, and our team was barrelling through last-minute updates to our robot controllers in a small conference room at the Michigan Tech Research Institute (MTRI) offices in Ann Arbor, Mich. That’s when we noticed the smell. We’d assumed that one of the benefits of entering a virtual disaster competition was that we wouldn’t be exposed to any actual disasters, but equipment in the basement of the building MTRI shares had started to smoke. We evacuated. The fire department showed up. And as soon as we could, the team went back into the building, hunkered down, and tried to make up for the unexpected loss of several critical hours.

Team BARCS joins the SubT Virtual Track
The smoke incident happened more than a year after we first learned of the DARPA Subterranean Challenge. DARPA announced SubT early in 2018, and at that time, we were interested in building internal collaborations on multi-agent autonomy problems, and SubT seemed like the perfect opportunity. Though a few of us had backgrounds in robotics, the majority of our team was new to the field. We knew that submitting a proposal as a largely non-traditional robotics team from an organization not known for research in robotics was a risk. However, the Virtual Track gave us the opportunity to focus on autonomy and multi-agent teaming strategies, areas requiring skill in asynchronous computing and sensor data processing that are strengths of our Institute. The prevalence of open source code, small inexpensive platforms, and customizable sensors has provided the opportunity for experts in fields other than robotics to apply novel approaches to robotics problems. This is precisely what makes the Virtual Track of SubT appealing to us, and since starting SubT, autonomy has developed into a significant research thrust for our Institute. Plus, robots are fun!

After many hours of research, discussion, and collaboration, we submitted our proposal early in 2018. And several months later, we found out that we had won a contract and became a funded team (Team BARCS) in the SubT Virtual Track. Now we needed to actually make our strategy work for the first SubT Tunnel Circuit competition, taking place in August of 2019.

Building a team of virtual robots
A natural approach to robotics competitions like SubT is to start with the question of “what can X-type robot do” and then build a team and strategy around individual capabilities. A particular challenge for the SubT Virtual Track is that we can’t design our own systems; instead, we have to choose from a predefined set of simulated robots and sensors that DARPA provides, based on the real robots used by Systems Track teams. Our approach is to look at what a team of robots can do together, determining experimentally what the best team configuration is for each environment. By the final competition, ideally we will be demonstrating the value of combining platforms across multiple Systems Track teams into a single Virtual Track team. Each of the robot configurations in the competition has an associated cost, and team size is constrained by a total cost. This provides another impetus for limiting dependence on complex sensor packages, though our ranging preference is 3D lidar, which is the most expensive sensor!

Image: Michigan Tech Research Institute

The teams can rely on realistic physics and sensors but they start off with no maps of any kind, so the focus is on developing autonomous exploratory behavior, navigation methods, and object recognition for their simulated robots.

One of the frequent questions we receive about the Virtual Track is if it’s like a video game. While it may look similar on the surface, everything under the hood in a video game is designed to service the game narrative and play experience, not require novel research in AI and autonomy. The purpose of simulations, on the other hand, is to include full physics and sensor models (including noise and errors) to provide a testbed for prototyping and developing solutions to those real-world challenges. We are starting with realistic physics and sensors but no maps of any kind, so the focus is on developing autonomous exploratory behavior, navigation methods, and object recognition for our simulated robots.

Though the simulation is more like real life than a video game, it is not real life. Due to occasional software bugs, there are still non-physical events, like the robots falling through an invisible hole in the world or driving through a rock instead of over it or flipping head over heels when driving over a tiny lip between world tiles. These glitches, while sometimes frustrating, still allow the SubT Virtual platform to be realistic enough to support rapid prototyping of controller modules that will transition straightforwardly onto hardware, closing the loop between simulation and real-world robots.

Full autonomy for DARPA-hard scenarios
The Virtual Track requirement that the robotic agents be fully autonomous, rather than have a human supervisor, is a significant distinction between the Systems and Virtual Tracks of SubT. Our solutions must be hardened against software faults caused by things like missing and bad data since our robots can’t turn to us for help. In order for a team of robots to complete this objective reliably with no human-in-the-loop, all of the internal systems, from perception to navigation to control to actuation to communications, must be able to autonomously identify and manage faults and failures anywhere in the control chain.

The communications limitations in subterranean environments (both real and virtual) mean that we need to keep the amount of information shared between robots low, while making the usability of that information for joint decision-making high. This goal has guided much of our design for autonomous navigation and joint search strategy for our team. For example, instead of sharing the full SLAM map of the environment, our agents only share a simplified graphical representation of the space, along with data about frontiers it has not yet explored, and are able to merge its information with the graphs generated by other agents. The merged graph can then be used for planning and navigation without having full knowledge of the detailed 3D map.

The Virtual Track requires that the robotic agents be fully autonomous. With no human-in-the-loop, all of the internal systems, from perception to navigation to control to actuation to communications, must be able to identify and manage faults and failures anywhere in the control chain.

Since the objective of the SubT program is to advance the state-of-the-art in rapid autonomous exploration and mapping of subterranean environments by robots, our first software design choices focused on the mapping task. The SubT virtual environments are sufficiently rich as to provide interesting problems in building so-called costmaps that accurately separate obstructions that are traversable (like ramps) from legitimately impassible obstructions. An extra complication we discovered in the first course, which took place in mining tunnels, was that the angle of the lowest beam of the lidar was parallel to the down ramps in the tunnel environment, so they could not “see” the ground (or sometimes even obstructions on the ramp) until they got close enough to the lip of the ramp to receive lidar reflections off the bottom of the ramp. In this case, we had to not only change the costmap to convince the robot that there was safe ground to reach over the lip of the ramp, but also had to change the path planner to get the robot to proceed with caution onto the top of the ramp in case there were previously unseen obstructions on the ramp.

In addition to navigation in the costmaps, the robot must be able to generate its own goals to navigate to. This is what produces exploratory behavior when there is no map to start with. SLAM is used to generate a detailed map of the environment explored by a single robot—the space it has probed with its sensors. From the sensor data, we are able to extract information about the interior space of the environment while looking for holes in the data, to determine things like whether the current tunnel continues or ends, or how many tunnels meet at an intersection. Once we have some understanding of the interior space, we can place navigation goals in that space. These goals naturally update as the robot traverses the tunnel, allowing the entire space to be explored.

Sending our robots into the virtual unknown
The solutions for the Virtual Track competitions are tested by DARPA in multiple sequestered runs across many environments for each Circuit in the month prior to the Systems Track competition. We must wait until the joint award ceremony at the conclusion of the Systems Track to find out the results, and we are completely in the dark about placings before the awards are announced. It’s nerve-wracking! The challenges of the worlds used in the Circuit events are also hand-designed, so features of the worlds we use for development could be combined in ways we have not anticipated—it’s always interesting to see what features were prioritized after the event. We test everything in our controllers well enough to feel confident that we at least are submitting something reasonably stable and broadly capable, and once the solution is in, we can’t really do anything other than “let go” and get back to work on the next phase of development. Maybe it’s somewhat like sending your kid to college: “we did our best to prepare you for this world, little bots. Go do good.”

Image: Michigan Tech Research Institute

The first SubT competition was the Tunnel Circuit, featuring a labyrinthine environment that simulated human-engineered tunnels, including hazards such as vertical shafts and rubble.

The first competition was the Tunnel Circuit, in October 2019. This environment models human-engineered tunnels. Two substantial challenges in this environment were vertical shafts and rubble. Our team accrued 21 points over 15 competition runs in five separate tunnel environments for a second place finish, behind Team Coordinated Robotics.

The next phase of the SubT virtual competition was the Urban Circuit. Much of the difference between our Tunnel and Urban Circuit results came down to thorough testing to identify failure modes and implementations of checks and data filtering for fault tolerance. For example, in the SLAM nodes run by a single robot, the coordinates of the most recent sensor data are changed multiple times during processing and integration into the current global 3D map of the “visited” environment stored by that robot. If there is lag in IMU or clock data, the observation may be temporarily registered at a default location that is very far from the actual position. Since most of our decision processes for exploration are downstream from SLAM, this can cause faulty or impossible goals to be generated, and the robots then spend inordinate amounts of time trying to drive through walls. We updated our method to add a check to see if the new map position has jumped a far distance from the prior map position, and if so, we threw that data out.

Image: Michigan Tech Research Institute

In open spaces like the rooms in the Urban circuit, we adjusted our approach to exploration through graph generation to allow the robots to accurately identify viable routes while helping to prevent forays off platform edges.

Our approach to exploration through graph generation based on identification of interior spaces allowed us to thoroughly explore the centers of rooms, although we did have to make some changes from the Tunnel circuit to achieve that. In the Tunnel circuit, we used a simplified graph of the environment based on landmarks like intersections. The advantage of this approach is that it is straightforward for two robots to compare how the graphs of the space they explored individually overlap. In open spaces like the rooms in the Urban circuit, we chose to instead use a more complex, less directly comparable graph structure based on the individual robot’s trajectory. This allowed the robots to accurately identify viable routes between features like subway station platforms and subway tracks, as well as to build up the navigation space for room interiors, while helping to prevent forays off the platform edges. Frontier information is also integrated into the graph, providing a uniform data structure for both goal selection and route planning.

The results are in!
The award ceremony for the Urban Circuit was held concurrently with the Systems Track competition awards this past February in Washington State. We sent a team representative to participate in the Technical Interchange Meeting and present the approach for our team, and the rest of us followed along from our office space on the DARPAtv live stream. While we were confident in our solution, we had also been tracking the online leaderboard and knew our competitors were going to be submitting strong solutions. Since the competition environments are hand-designed, there are always novel challenges that could be presented in these environments as well. We knew we would put up a good fight, but it was very exciting to see BARCS appear in first place!

Any time we implement a new module in our control system, there is a lot of parameter tuning that has to happen to produce reliably good autonomous behavior. In the Urban Circuit, we did not sufficiently test some parameter values in our exploration modules. The effect of this was that the robots only chose to go down small hallways after they explored everything else in their environment, which meant very often they ran out of time and missed a lot of small rooms. This may be the biggest source of lost points for us in the Urban Circuit. One of our major plans going forward from the Urban Circuit is to integrate more sophisticated node selection methods, which can help our robots more intelligently prioritize which frontier nodes to visit. By going through all three Circuit challenges, we will learn how to appropriately add weights to the frontiers based on features of the individual environments. For the Final Challenge, when all three Circuit environments will be combined into large systems, we plan to implement adaptive controllers that will identify their environments and use the appropriate optimized parameters for that environment. In this way, we expect our agents to be able to (for example) prioritize hallways and other small spaces in Urban environments, and perhaps prioritize large openings over small in the Cave environments, if the small openings end up being treacherous overall.

Next for our team: Cave Circuit
Coming up next for Team BARCS is the Virtual Cave Circuit. We are in the middle of testing our hypothesis that our controller will transition from UGVs to UAVs and developing strategies for refining our solution to handle Cave Circuit environmental hazards. The UAVs have a shorter battery life than the UGVs, so executing a joint exploration strategy will also be a high priority for this event, as will completing our work on graph sharing and merging, which will give our robot teams more sophisticated options for navigation and teamwork. We’re reaching a threshold in development where we can start increasing the “smarts” of the robots, which we anticipate will be critical for the final competition, where all of the challenges of SubT will be combined to push the limits of innovation. The Cave Circuit will also have new environmental challenges to tackle: dynamic features such as rock falls have been added, which will block previously accessible passages in the cave environment. We think our controllers are well-poised to handle this new challenge, and we’re eager to find out if that’s the case.

As of now, the biggest worries for us are time and team composition. The Cave Circuit deadline has been postponed to October 15 due to COVID-19 delays, with the award ceremony in mid-November, but there have also been several very compelling additions to the testbed that we would like to experiment with before submission, including droppable networking ‘breadcrumbs’ and new simulated platforms. There are design trade-offs when balancing general versus specialist approaches to the controllers for these robots—since we are adding UAVs to our team for the first time, there are new decisions that will have to be made. For example, the UAVs can ascend into vertical spaces, but only have a battery life of 20 minutes. The UGVs by contrast have 90 minute battery life. One of our strategies is to do an early return to base with one or more agents to buy down risk on making any artifact reports at all for the run, hedging against our other robots not making it back in time, a lesson learned from the Tunnel Circuit. Should a UAV take on this role, or is it better to have them explore deeper into the environment and instead report their artifacts to a UGV or network node, which comes with its own risks? Testing and experimentation to determine the best options takes time, which is always a worry when preparing for a competition! We also anticipate new competitors and stiffer competition all around.

Image: Michigan Tech Research Institute

Team BARCS has now a year to prepare for the final DARPA SubT Challenge event, expected to take place in late 2021.

Going forward from the Cave Circuit, we will have a year to prepare for the final DARPA SubT Challenge event, expected to take place in late 2021. What we are most excited about is increasing the level of intelligence of the agents in their teamwork and joint exploration of the environment. Since we will have (hopefully) built up robust approaches to handling each of the specific types of environments in the Tunnel, Urban, and Cave circuits, we will be aiming to push the limits on collaboration and efficiency among the agents in our team. We view this as a central research contribution of the Virtual Track to the Subterranean Challenge because intelligent, adaptive, multi-robot collaboration is an upcoming stage of development for integration of robots into our lives.

The Subterranean Challenge Virtual Track gives us a bridge for transitioning our more abstract research ideas and algorithms relevant to this degree of autonomy and collaboration onto physical systems, and exploring the tangible outcomes of implementing our work in the real world. And the next time there’s an incident in the basement of our building, the robots (and humans) of Team BARCS will be ready to respond.

Richard Chase, Ph.D., P.E., is a research scientist at Michigan Tech Research Institute (MTRI) and has 20 years of experience developing robotics and cyber physical systems in areas from remote sensing to autonomous vehicles. At MTRI, he works on a variety of topics such as swarm autonomy, human-swarm teaming, and autonomous vehicles. His research interests are the intersection of design, robotics, and embedded systems.

Sarah Kitchen is a Ph.D. mathematician working as a research scientist and an AI/Robotics focus area leader at MTRI. Her research interests include intelligent autonomous agents and multi-agent collaborative teams, as well as applications of autonomous robots to sensing systems.

This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Contract No. HR001118C0124 and is released under Distribution Statement (Approved for Public Release, Distribution Unlimited). Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of DARPA. Continue reading

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