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.

中文翻译：

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基于改进的 Q 学习算法的半被动机器人行走控制

被动双足机器人的稳定性分析与控制因其独特的特点一直是人们深入研究的课题。这项工作针对被动机器人行走过程碰撞阶段施加在足部的力给出了一个新的视角，是一种不同于以往的施加冲击力的全新方式。因此，由于该力与支撑腿不平行，推导了新的方程，为研究提供进一步的分析。此外，本文将被动行走的特点与强化学习的过程相结合，设计了一种改进的算法来计算控制力的值。仿真结果表明，本文设计的控制方法不仅能够使非定常被动机器人实现稳定行走，而且具有较快的控制速度。此外，该方法扩大了初始值的选择范围，为后续的研究工作提供了方便的参考。