Robot Videos: Robot With Bird Legs, DARPA Manipulation Demo, and Darwin-OP's Dance Moves

In this edition of our video-filled Friday post, we present you a robot with bird-inspired legs, a demo of DARPA's ARM program, and a Darwin-OP humanoid learning to play Dance Dance Revolution

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Robot Videos: Robot With Bird Legs, DARPA Manipulation Demo, and Darwin-OP's Dance Moves

See this? It's a robot with bird legs. Genius. This, plus a manipulation arm from DARPA and a Darwin-OP humanoid getting learning to play Dance Dance Revolution, in this edition of our more or less reliable (it's less) video-filled Friday post.

First up, and for the life of me I don't know how we missed this thing at IEEE International Conference on Intelligent Robots and Systems back in September, is this quadrotor with giant spindly bird legs from the Utah Telerobotics Lab. It's a passive system that uses the weight of the robot to actuate the grippers, so that when the quadrotor lands on something it latches on and stays. To release, the robot just lifts off, and the grippers let go. Birds use a very similar system to keep themselves perched while asleep, and the leg and toe design was inspired directly by songbirds.

Incidentally, the quad does fly with these things hanging off of it: you can see a video of it in the air (but not perching) here.

[ Utah Telerobotics Lab ]

Last July, Darwin-OP had just started learning how to use a Dance Dance Revolution-stye pad, and we're happy to report that Paul Fredrickson at Purdue has managed to teach the robot to visually recognize symbols from the game and respond to them with the appropriate pad actuation. We've been promised more detail in a follow-up vid in the near future, and we're keeping our fingers crossed for an operational version that can destroy humans at a real round of DDR some time soon.

[ Purdue ]

And finally we've got this video from DARPA's ARM program. ARM stands for Autonomous Robotic Manipulation, and the program has been running for several years now using relatively inexpensive off-the-shelf hardware to perform human-ish tasks like opening doors and using tools. In open-source tests from November of last year, the best teams achieved a 93 percent success rate in grasping both modeled and "unmodeled" objects.


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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

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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