From Walking to Jumping: Precise Gait Control in Bipedal Robots via Model Predictive Control

抄録

In this study, we propose a method based on the Model Predictive Control (MPC) framework for generating dynamic gaits for bipedal robots. Utilizing the Crocoddyl optimization library, we designed and implemented an optimization strategy that minimizes a predefined cost function while satisfying the robot's dynamic constraints. Experimental results show that our method can effectively generate various gaits, including walking, jumping, and standing, demonstrating the potential of this approach in motion planning and control for bipedal robots.