Mimicking Human Push-Recovery Strategy based on Five-Mass with Angular Momentum Model

As humanoid robots start entering to the human beings environments, the collision between the robot and other objects is inevitable. To solve this problem, we propose the human mimicking push-recovery strategy. With the arm mechanism, the humanoid robot utilizes human-like strategies to deal with the unexpected collision. We analyse the human push-recovery movement to the external force. Thus we can design the trajectory generator to mimic human beings reactions. To reduce the modelling error and improve zmp stability, we utilizes the five-mass with angular momentum model as humanoid robot model. We design the safe bound examination and the Center of Mass (COM) state estimator to judge the collision stage. The safe bound examination is used to guarantee the walking stability. Moreover, the COM state estimator is used to determine whether the pushing is over or not. The push-recovery control system is implemented on the humanoid robot developed in our NTU-iCeiRA lab. The purpose of this paper aims to integrate different push-recovery strategies while encountering different collision conditions based on the five-mass with angular momentum model.