Real-time Trajectory Optimization and Control for Ball Bumping with Quadruped Robots

Abstract

This paper studies real-time motion planning and control for ball bumping motion with quadruped robots. To enable the quadruped to bump the flying ball with different initializations, we develop a nonlinear trajectory optimization based planning scheme that jointly identifies the take-off time and state to achieve accurate ball hitting during flight phase. Such a planning scheme employs a two-dimensional single rigid body model that achieves a satisfactory balance between accuracy and efficiency for the highly time-sensitive task. To precisely execute the planned motion, tracking controller needs to incorporate the strict time-state constraint imposed on the take-off and ball hitting events. To this end, we develop an improved model predictive controller that respects the critical time-state constraints. The proposed planning and control framework is validated with a real Aliengo robot. Experiments show that the problem planning approach can be computed in approximately $60$ ms on average, enabling successful accomplishment of the ball bumping motion with various initializations in real time.