Boston Dynamics Gets $10 Million from DARPA for New Stealthy, Bulletproof LS3

DARPA wants the next generation LS3 robotic mule to be quiet, rugged, and ready for action

2 min read
Boston Dynamics Gets $10 Million from DARPA for New Stealthy, Bulletproof LS3

You'd think that Boston Dynamics would be all kinds of busy building (and supporting) a small army of Atlas robots for the DARPA Robotics Challenge. But, it looks like they've somehow managed to find the time to continue working on all of their other systems as well, like BigDog's big brother, LS3. Last week, DARPA committed to investing an extra $10 million towards a more robust and (eventually) deployable robot.

DARPA is very specific about what they want to see in the next-gen LS3, namely:

...the development of an enhanced version of the LS3 system with increased reliability and usability, enhanced survivability against small arms fire and a quiet power supply to support stealthy tactical operations.

It's no surprise that quiet power supply is on that list, since LS3's gas-powered hydraulic pump sounds like a swarm of angry bees, if the bees were the size of domestic cats. However, finding a power supply that can keep LS3 running all day isn't going to be easy; it's very hard to match the power density (and general availability) of liquid fuel. One option might be to turn LS3 into a hybrid, giving it a sort of temporary on-demand "stealth mode."

Survivability is also an important step towards deployment. As we've seen, LS3 is reasonably well protected from any trouble that it might get itself into (running into trees, falling into ditches, that sort of thing). It does have some vulnerable spots, though, like all of those complicated (and expensive) head sensors, and we imagine that some of the hydraulics might not react well to being shot either. LS3 isn't designed for combat (videos like these notwithstanding), but if it's to be useful in a gear-hauling capacity, there'll certainly be some risk to the robot, and it would be a shame if a single well-placed round could pit it out of commission.

The estimated completion date for this new part of the contract is March 31, 2015, but we probably shouldn't read too much into that. And anyway, we're secretly (not so secretly anymore) hoping to be riding an LS3 around our neighborhood well before then.

[ Boston Dynamics ] via [ ]

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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

“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.

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

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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