Active Dynamic Load Adaptation for Quadruped Locomotion on Complex Terrain

Abstract

Quadruped robots show important potential for load carrying tasks due to their terrain adaptability, and a unique challenge of these tasks is to maintain quadrupedal stability when the load has active and dynamic characteristics. Their mass and center of mass change dynamically, rather than being integrated as a whole-body component of the quadruped. Unlike traditional load-carrying tasks, where the load is typically passive and its influence on the robot's movement is predictable and static, active dynamic loads can actively alter the robot's balance control in real-time, posing load disturbances to locomotion. These load disturbances, when combined with the fundamental attitude changes induced by complex terrain, create dual dynamic disturbances for the robot. To address these dual disturbances, we propose an active dynamic load modeling approach that captures the active and dynamic characteristics of the load, enabling the robot to adapt to the real-time changes in load movement. This approach is integrated into a Reinforcement Learning (RL) framework that leverages dynamic models: an Inverse Dynamic Model (IDM) that learns the dynamic characteristics of the active load, and a Forward Dynamic Model (FDM) that predicts the effects of complex terrain on the robot's motion, enabling synchronous adaptation to both types of dynamic disturbances. Extensive comparative simulations and physical experiments across diverse terrains, with active dynamic loads of varying movements, demonstrate the effectiveness of our method in enhancing balance control and adaptability.