Gibbot Training to Swing Like a Monkey

A two-dimensional swinging robot that's learning monkey gaits to (eventually) perform gymnastics

2 min read
Gibbot Training to Swing Like a Monkey

This purple little guy is the Gibbot, a robot designed by the Laboratory for Intelligent Mechanical Systems at Northwestern University to explore a particular type of locomotion that's been perfected by monkeys* to quickly and efficiently get around in trees.

Astute and loyal followers of IEEE Spectrum might remember ParkourBot, a two-dimensional gymnast robot also from Northwestern (in collaboration with Carnegie Mellon). ParkourBot is a pro at bouncing up and down walls, but it's not great at going sideways. The Gibbot, on the other hand, is designed primarily to investigate horizontal locomotion. Specifically, the Gibbot is intended to brachiate, which is a type of highly efficient motion used by (surprise!) gibbons.

Brachiation is essentially repetitive horizontal swinging: there's no net vertical motion, which means that the gibbon doesn't really have to expend much in the way of energy fighting gravity. Once it gets going, the gibbon can move very fast by just grabbing on and letting go at the right times. Figuring out what these times are (and what gaits they result in) is the tricky part, but the researchers were able to show off some successes:

The Gibbot itself consists of two arms with electromagnets at the ends and one powered joint in the middle. It swings around on a steel wall, which provides an unlimited number of clamping points for the magnets. This allows for the testing and comparison of a variety of different brachiating gaits, with a fairly ambitious (and awesome) goal in mind, according to the paper: "by employing a diverse suite of gaits, the Gibbot will be able to perform gymnastic maneuvers to reach specific handholds in the environment." Gymnastic maneuvers, you say? We can't wait.

Stable Open-Loop Brachiation on a Vertical Wall, by Nelson Rosa Jr., Adam Barber, Robert D. Gregg, and Kevin M. Lynch from Northwestern University, was presented this month at the 2012 IEEE International Conference on Robotics and Automation in St. Paul, Minn.

[ Laboratory for Intelligent Mechanical Systems ]

*Before anybody sends us death threats, please rest assured that we are well aware that gibbons are apes and not monkeys.

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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
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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