DCM-based dynamic stable walking under terrain-induced time-varying disturbances for humanoid robots

When humanoid robots attempt to walk on terrain such as shaking platforms, time-varying disturbances are introduced to the support foot. These abrupt changes of inclination angle can cause the robot to lose balance upon landing, presenting significant challenges for balance control algorithms. To address this issue, we propose a novel divergent component of motion(DCM)-based time-varying disturbance walking(DCM-TVDW) method. This method allows the robot to walk on rugged surfaces and helps to maintain dynamic balance when subjected to large time-varying disturbances. In the DCM-TVDW control method,we first adjust the robot's center of mass and stride height to adapt to transitions between different terrain types via a variable height stabilization method, and hold these quantities constant as base values. We then combine DCM with the N-step capturability strategy. This combination allows for dynamic balance through multi-step adjustments from the initially unstable region, thereby extending the robots stability boundary. Simulation and experimental results demonstrate that the DCM-TVDW method enables the SJ-Bruce robot to traverse a dynamically shaking platform with an inclination angle of approximately 22°.