Optimal Control of Quadruped Robot Using HQP-Based Virtual Model Control

摘要

This paper proposes a virtual model control framework based on hierarchical quadratic programming to achieve the optimal distribution of foot forces for a quadruped robot. The framework comprises the optimal force distribution of the support phase and acceleration adaptive virtual stiffness control of the swing phase. In the support phase, the optimal distribution of the foot force is transformed into a hierarchical quadratic programming problem. The goal is to achieve task priority coordination in different stages of the support phase. The mapping relationship between the ground reaction force on the foot and the virtual force on the torso is used for this purpose. In the swing phase, the virtual stiffness is adaptively adjusted to improve the trajectory tracking performance according to the acceleration demand of the foot trajectory tracking. Simulation experiments demonstrate that the robot performs trot and other gaits with significant stability improvement, and the results validate the feasibility and effectiveness of the proposed control framework.