Velocity Tracking Control for Bipedal Robot Based on Model Predictive Control

Velocity tracking control plays a crucial role in bipedal robots, especially with under-actuated characteristics. This paper proposed a velocity tracking control algorithm based on model predictive control for the parallel five-link point-footed robot XingT, which is designed for heavy-duty. Specifically, in order to reduce the computational complexity caused by the complete dynamic model, this paper used the linear inverted pendulum model to predict the robot's foot placement to ensure stable velocity tracking control. Combined with model predictive control, the optimal foot placement was obtained based on the robot's state during several consecutive gait cycles. The proposed method was successfully applied to XingT in the simulation environment and can maintain stable tracking of the desired velocity under step commands, time-varying commands, and external force disturbances at a maximum speed of 0.2 {m} / {s}.