Tracking the walking gait of a novel quadruped robot with soft actuators using model predictive control

Quadruped robots are used in various scenarios, but their rigid structure limits their applications. In contrast, soft structures offer greater flexibility, adaptability, and lower costs but struggle with motion modeling and control stability. This paper proposes a novel design of a quadruped robot that uses soft actuators driven by tendons for joint movement. Firstly, kinematic principles are applied to model single-leg movements; subsequently, a data-driven approach is proposed to model the soft actuator by integrating the control principle with the single-leg structure. Furthermore, a system identification-based approach is proposed for parameter estimation. Ultimately, the model predictive control method is effectively employed to track the predefined gait during locomotion. Experimental results demonstrate that the robot designed can walk smoothly and follow the preset gait accurately.