Tencent’s New Wheeled Robot Flicks Its Tail To Do Backflips

Ollie’s wheels, legs, and tail allow it to balance, flip, manage stairs, and deliver coffee

2 min read
A black and white robot with four legs: each pair of legs is joined by an axle supporting a wheel. A wheeled tail is tucked up under the body.
Photo: Tencent

Ollie (I think its name is Ollie) is a “a novel wheel-legged robot” from Tencent Robotics. The word “novel” is used quite appropriately here, since Ollie sports some unusual planar parallel legs atop driven wheels. It’s also got a multifunctional actuated tail that not only enables some impressive acrobatics, but also allows the robot to transition from biped-ish to triped-ish to stand up extra tall and support a coffee-carrying manipulator.

It’s a little disappointing that the tail only appears to be engaged for specific motions—it doesn’t seem like it’s generally part of the robot’s balancing or motion planning, which feels like a missed opportunity. But this robot is relatively new, and its development is progressing rapidly, which we know because an earlier version of the hardware and software was presented at ICRA 2021 a couple weeks back. Although, to be honest with you, there isn’t a lot of info on the new one besides the above video, so we’ll be learning what we can from the ICRA paper.

The paper is mostly about developing a nonlinear balancing controller for the robot, and they’ve done a bang-up job with it, with the robot remaining steady even while executing sequences of dynamic motions. The jumping and one-legged motions are particularly cool to watch. And, well, that’s pretty much it for the ICRA paper, which (unfortunately) barely addresses the tail at all, except to say that currently the control system assumes that the tail is fixed. We’re guessing that this is just a symptom of the ICRA paper submission deadline being back in October, and that a lot of progress has been made since then.

Seeing the arm and sensor package at the end of the video is a nod to some sort of practical application, and I suppose that the robot’s ability to stand up to reach over that counter is some justification for using it for a delivery task. But it seems like it’s got so much more to offer, you know? Many far more boring platforms robots could be delivering coffee, so let’s find something for this robot to do that involves more backflips.

Balance Control of a Novel Wheel-legged Robot: Design and Experiments, by Shuai Wang, Leilei Cui, Jingfan Zhang, Jie Lai, Dongsheng Zhang, Ke Chen, Yu Zheng, Zhengyou Zhang, and Zhong-Ping Jiang from Tencent Robotics X, was presented at ICRA 2021.

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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

“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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