Balancing Control and Pose Optimization for Wheel-legged Robots Navigating High Obstacles
This addresses the challenge of terrain navigation for wheel-legged robots, offering an incremental improvement in control methods for specific locomotion tasks.
The paper tackles the problem of controlling wheel-legged quadrupedal robots to navigate high obstacles like stairs by proposing a method combining pose optimization and force control via quadratic programming, achieving the capability to roll over a 0.36 m obstacle and traverse multiple stairs without leg lifting or collisions.
In this paper, we propose a novel approach on controlling wheel-legged quadrupedal robots using pose optimization and force control via quadratic programming (QP). Our method allows the robot to leverage the whole-body motion and the wheel actuation to roll over high obstacles while keeping the wheel torques to navigate the terrain while keeping the wheel traction and balancing the robot body. In detail, we first present a linear rigid body dynamics with wheels that can be used for real-time balancing control of wheel-legged robots. We then introduce an effective pose optimization method for wheel-legged robot's locomotion over steep ramp and stair terrains. The pose optimization solves for optimal poses to enhance stability and enforce collision-fee constraints for the rolling motion over stair terrain. Experimental validation on the real robot demonstrated the capability of rolling up on a 0.36 m obstacle. The robot can also successfully roll up and down multiple stairs without lifting its legs or having collision with the terrain.