Walking Control of Semi-Passive Robot Via a Modified Q-Learning Algorithm

The analysis and control of stability of passive biped robot has been the subject of an in-depth study because of its unique characteristics. This work gives a new perspective aiming at a force applied on foot of collision phase of walking process of passive robot, which is a completely new way of applying impulse force that is different from the previous. Therefore, the new equation has been derived due to this force which is not parallel to the support leg to provide further analysis for the study. Besides, this paper combines the characteristics of passive walking with the process of reinforcement learning, and an improved algorithm thus was designed to calculate the value of the control force. The simulation results show that control method designed in this article can not only make the unsteady passive robot achieve stable walking, but also have a quick control speed. Furthermore, the selection range of initial values is expanded by using this method, which provides a convenient reference for the later research work.