Resistant Compliance Control for Biped Robot Inspired by Humanlike Behavior
Qiang Huang, Chencheng Dong, Zhangguo Yu, Xuechao Chen, Qingqing Li, Huanzhong Chen, Huaxin Liu
Abstract
Compliance control is important for the realization of disturbance absorption in biped robots. However, under a sustained disturbance, compliance control causes the robot’s balance to deteriorate because of its floating base nature. Humans address this problem by resisting external disturbance. When pushed, a human will reconcile their posture with the applied external force and then push back to maintain balance. Inspired by this behavior, we propose a compliance control strategy for biped robots called resistant compliance, which allows a robot to comply with the external disturbance initially and then repel the disturbance to reduce the imbalance caused by the reconciliatory motion. As a result, the robot can obtain improved environment-interaction stability and react more like a typical human, thus making both its locomotion and its interactions more stable and safer. To realize this control strategy, the virtual-mass-model (VMM) control is redesigned to unify the disturbances from unexpected external forces and an inclined floor. Then, the VMM control is combined with the linear-inverted-pendulum model to realize resistant compliant motion. Model predictive control is used to track the reference zero-moment-point trajectory, which is essential for locomotion. To validate the proposed control strategy, the method is implemented on the human-sized humanoid robot BHR-T.