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NASA Announces Space Robotics Challenge Finalists

Top teams will compete in a simulated Mars mission

2 min read
NASA Valkyrie Humanoid Robot
NASA's Valkyrie humanoid robot.
Image: NASA

Last August, NASA opened the first round of the Space Robotics Challenge. A follow-on to the DARPA Robotics Challenge, the SRC is focused on what it’s going to take to get humans back to the moon or on to Mars, embracing the idea that sending humanoid robots there first would make everything a heck of a lot easier. Just like the DRC, the SRC starts in simulation, with an initial round to select 20 finalists from 93 competing teams. NASA has just announced the results.

In order to make it into one of the 20 finalist slots, teams had to perform some simple tasks in simulation (using Gazebo) as quickly as possible. They had to correctly identify a series of simulated blinking lights, and then push a button with a simulated R5 Valkyrie and walk 1 meter through a door without falling over.

All 20 teams have equal standing as they move on to the final round of the competition, but here are the top five in order of how amusing I find their team names:

  • BIT PLEASE
  • THE HUMANZ ARE DEAD
  • Walk Softly
  • Ring of the Nibelungs
  • Nevermore

The other 15 somewhat-less-creatively-named finalist teams are, in alphabetical order:

  • Coordinated Robotics
  • Mingo Mountain Robotics
  • MITs
  • Mystic
  • Sirius
  • SpaceBucs
  • Space Weavers
  • Team AL v.2.0
  • Team Olrun
  • Team Olympus Mons
  • Whalers
  • WPI Humanoid Robotics Lab
  • WV Robotics Team
  • Xion Systems
  • ZARJ

NASA tells us that 16 of these teams are based in the United States. There’s one Canadian team, one team from Japan, one mixed team from the U.S./U.K./Germany, and one horribly timezone-challenged mixed team from Spain/Scotland/Canada/Australia. The largest team has 39 members and the smallest has just a single person, and a full half of the teams have no specific affiliation, which is pretty cool.

The SRC Finals themselves will take place between June 13 and June 17—check out our earlier post for more details on that. In the meantime, NASA is hosting a space robotics webinar which actually looks interesting, a thing that I don’t think I’ve ever said about a webinar before. It’s next week, and you can sign up here.

[ NASA SRC ]

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How the U.S. Army Is Turning Robots Into Team Players

Engineers battle the limits of deep learning for battlefield bots

11 min read
Robot with threads near a fallen branch

RoMan, the Army Research Laboratory's robotic manipulator, considers the best way to grasp and move a tree branch at the Adelphi Laboratory Center, in Maryland.

Evan Ackerman
LightGreen

This article is part of our special report on AI, “The Great AI Reckoning.

"I should probably not be standing this close," I think to myself, as the robot slowly approaches a large tree branch on the floor in front of me. It's not the size of the branch that makes me nervous—it's that the robot is operating autonomously, and that while I know what it's supposed to do, I'm not entirely sure what it will do. If everything works the way the roboticists at the U.S. Army Research Laboratory (ARL) in Adelphi, Md., expect, the robot will identify the branch, grasp it, and drag it out of the way. These folks know what they're doing, but I've spent enough time around robots that I take a small step backwards anyway.

The robot, named RoMan, for Robotic Manipulator, is about the size of a large lawn mower, with a tracked base that helps it handle most kinds of terrain. At the front, it has a squat torso equipped with cameras and depth sensors, as well as a pair of arms that were harvested from a prototype disaster-response robot originally developed at NASA's Jet Propulsion Laboratory for a DARPA robotics competition. RoMan's job today is roadway clearing, a multistep task that ARL wants the robot to complete as autonomously as possible. Instead of instructing the robot to grasp specific objects in specific ways and move them to specific places, the operators tell RoMan to "go clear a path." It's then up to the robot to make all the decisions necessary to achieve that objective.

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