Climbing Robot Tank Can Corner Like a Gecko

This dry-adhesion tankbot can transition from horizontal to vertical surfaces and back again

2 min read
Climbing Robot Tank Can Corner Like a Gecko

This is not the first sticky-treaded robotank, but as far as I know, it's the first one that can manage to go around corners and make that tricky transition from horizontal to vertical. The somewhat unfortunately named "Tailless Timing Belt Climbing Platform" (or TBCP-11) comes from Simon Frasier University way up there in Canada. It weighs 240 grams, and has no problems climbing up whiteboards, glass, and other slick surfaces.

The sticking power of those treads comes from the same handy little Van der Waals forces that geckos use to effortlessly stick to, well, everything. Instead of tiny hairs, though, TBCP-11 uses tiny mushrooms, which provide a substantial amount of conformable surface area for the robot to use to adhere to walls.

Maximizing compliant surface area has been an issue for gecko-type (aka dry-adhesion) climbing robots for a long time; the material itself is spectacular, but the tough part is getting enough of the material to make contact with your climbing surface. For example, check out the picture of Stickybot III's toes in this article, and notice how little of the adhesive the robot is relying on to stick. This is one of the advantages of the TBCP-11: the continuous loops of adhesive material provide a lot of adhesion power.

While this robot does have some autonomous capability, it's still tethered for power, since batteries are heavy. It's going to take a little extra work to increase the strength of the adhesive so that the TBCP-11 can bring its power source onboard, and the SFU researchers are also trying to figure out how to get the thing to turn without the treads coming loose and causing the TBCP-11 to plummet to its doom.

[ SFU ] via [ Vancouver Sun ]

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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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