Model-Based Control Implementation of Quadruped Robots With MuJoCo

Control algorithms rely on robot simulation platforms to evaluate the dynamics of the controlled robot. For legged robot simulators, the ability to handle contact and friction is fundamental. Many robot simulation platforms are designed for virtual prototyping, replicating the kinematics, dynamics, and real-world interactions of robotic systems. Among them, MuJoCo stands out. Despite MuJoCo’s widespread use in the literature, detailed documentation on the settings required for implementing model-based control techniques is lacking. We present the implementation of inverse dynamics impedance control within a locomotion control framework based on compliant foot trajectory tracking. We provide the theoretical foundation for defining the system model and control scheme, and explain how to extract the corresponding terms from MuJoCo. The settings for contact parameters and the computation of contact forces are detailed, with each linked to the corresponding theoretical background. To illustrate MuJoCo’s practicality, we present an application featuring a quadruped robot modeled on the MIT Mini Cheetah. We analyze and simulate how contact parameters affect the dynamics of the controlled robot. Finally, videos showcase simulations of the controlled quadruped robot, highlighting the effects of varying contact parameter values on contact dynamics.