Boston Dynamics' Marc Raibert On The Future Of BigDog

The founder of Boston Dynamics discusses the current progress and future plans for his favorite pet, the BigDog quadruped robot

2 min read

Back in May (I think, although the video wasn’t posted until now), Marc Raibert, founder of Boston Dynamics, gave a talk at Stanford on the current progress and future plans for BigDog. It’s an over an hour long, but (as you might expect) the juicy bits come in towards the end regarding the future plans. If you don’t have an hour or so, I’d recommend starting in at about the 46:50 mark, where you get to see some video of a quieter BigDog with an electric motor, among other things. If you don’t have time for even that, here’s a summary of what I thought were the most interesting bits:

-Marc Raibert says he’s inspired by mountain goats, which is pretty daunting when you’re designing a quadrupedal robot.

-Robots vs. mules: mules are better, except: they can only carry about a third of their body weight, they don’t take direction well, and they’re not easy to warehouse.

-That video of BigDog slipping on ice and recovering? It wasn’t programmed specifically to deal with slippery surfaces, and they didn’t even know it was icy out, they were just shooting some other test video and it happened to cross a patch of ice, recovering using its standard dynamic balance programming.

-BigDog is able to run (actually run, including a stride phase without any ground contact) at a little bit over 6 mph, although they’re still working on its balance while running.

-Boston Dynamics has two working BigDogs, both of which you can see in action at 30:40 (this is new video). Raibert wants to get 7 or 8 of them together to go dog sledding (!).

-BigDog can’t yet get up on its own, but they’re working on it… The next generation will have the hip (or shoulder) joints positioned outside of the body and higher up, with an increased range of motion that will allow the robot to get its legs under its body, which the current generation can’t do.

-Kinematically, the orientation of BigDog’s legs (knee front or knee back) just doesn’t matter. They’re able to take the legs off and swap them around.

-The noise BigDog makes is “much worse” in person. The videos “don’t do it justice.”

-Electric motor BigDog still sounds like bees (although they’ll be able to mute it completely), only runs for 10 minutes, and is slightly underpowered… They’re contemplating a “hybrid” version, where you can switch to silent operation for 10 minutes and then back to gas.

-BigDog can follow people autonomously using a scanning LIDAR system, engineers say it’s “really scary to have the robot following you going down hills” (ha!).

-There’s no redundancy in the walking system, “BigDog goes down when you shoot off a leg.”

-The biggest challenge so far has been making the system able to run in the heat (due to the engine).

There’s also a little bit of an update on PETMAN; unfortunately, the outtakes weren’t approved for webcast (neither, for that matter, were the BigDog outtakes. FROWNY FACE.). But you do get to see a CAD rendering of PETMAN:

Marc says PETMAN freaks him out a little bit because of the whole Uncanny Valley thing, but he’s trying to be mindful of that while designing PETMAN.

At the end, Marc Raibert even gives a shout-out to that brilliant BigDog parody video… He says that his new metric is how many views his BigDog YouTube videos (and their parodies) receive.

[ Boston Dynamics BigDog ]
[ Stanford @ YouTube ]

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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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