Cascade Trajectory Optimization with Phase Duration Adaption and Control for Wheel-Legged Robots Overcoming High Obstacles

摘要

In this paper, we propose a framework that contains a cascade trajectory optimization (CTO) method and a hybrid control architecture for wheel-legged quadruped robots. Our framework allows the robot to go over high obstacles efficiently without pause in body movement and maintain stability simultaneously. In detail, the CTO is first presented for planning the support motion of the entire process over obstacles. The CTO is used to optimize the body states, the locations and contact forces of the end-effector (EE) for each leg in the support state, and the duration of the phase, with multiple constraints taken into count. Then, the output of the CTO is reprocessed to connect the support motion with the swing part for generalizing the final trajectory. A hybrid control architecture consisting of body motion control, EE control, and swing leg control is designed to track the reprocessed trajectory. Validation in simulation demonstrates that our wheel-legged robot can overcome high obstacles up to 0.90m, showing the feasibility of this framework.