Rough Terrain Locomotion of a Leg-Wheel Robot with Predictive Event Driven Gait

Abstract

A leg-wheel robot has mechanically separated legs and wheels, and it performs high mobility and stability on rough terrains. In the first part of this paper, we propose a gait algorithm, which allows continuous locomotion of the robot under the random velocity command by a human operator. The gait algorithm, which uses predictive control, determines the timing of the legs' lifting to avoid the legs reaching the border of the work space. The predictive control is based on the comparison between the time necessary to return the support legs and the time left before they reach the border of the work space. In the second part, a velocity limitation method for the gait algorithm is discussed. This method limits the velocity command when it exceeds the mechanical specifications of the robot. Combined the velocity limitation method with the gait algorithm, it ensures the continuity of locomotion, and gives the efficient gait pattern with a long step length and low frequency of leg phase change. The proposed algorithms are evaluated by simulation and experiments on rough terrain.