Keep Rollin' - Whole-Body Motion Control and Planning for Wheeled Quadrupedal Robots

TL;DR

This paper presents a novel optimization-based control framework for wheeled quadrupedal robots that seamlessly integrates walking and driving, enabling robust, dynamic, and efficient locomotion across various terrains.

Contribution

It introduces a zero-moment point based motion optimization that incorporates wheel constraints and a hierarchical controller for whole-body motion planning and execution.

Findings

Achieved stable locomotion on flat, inclined, and stepped terrains.

Demonstrated 4 m/s speed with 83% reduction in transport cost.

Enabled more robust and dynamic movement compared to other wheeled-legged robots.

Abstract

We show dynamic locomotion strategies for wheeled quadrupedal robots, which combine the advantages of both walking and driving. The developed optimization framework tightly integrates the additional degrees of freedom introduced by the wheels. Our approach relies on a zero-moment point based motion optimization which continuously updates reference trajectories. The reference motions are tracked by a hierarchical whole-body controller which computes optimal generalized accelerations and contact forces by solving a sequence of prioritized tasks including the nonholonomic rolling constraints. Our approach has been tested on ANYmal, a quadrupedal robot that is fully torque-controlled including the non-steerable wheels attached to its legs. We conducted experiments on flat and inclined terrains as well as over steps, whereby we show that integrating the wheels into the motion control and planning framework results in intuitive motion trajectories, which enable more robust and dynamic locomotion compared to other wheeled-legged robots. Moreover, with a speed of 4 m/s and a reduction of the cost of transport by 83 % we prove the superiority of wheeled-legged robots compared to their legged counterparts.