A foot positioning compensator is developed in this paper for a full-body humanoid to retrieve its balance during continuous walking. An online Foot Position Compensator (FPC) is designed to improve the robustness of biped walking, which can modify predefined step position and step duration online with sensory feedback. Foot placement parameters are learned by the FPC based on the Policy Gradient Reinforcement Learning (PGRL) method. Moreover, the FPC assists the humanoid robot in rejecting external disturbances and recovering the walking position by re-planning the trajectories of walking pattern and the Center of Mass (CoM). An upper body pose control strategy is also presented to further enhance the performance of humanoid robots to overcome strong external disturbances. The advantages of this proposed method are that it neither requires prior information about the walking terrain conditions, nor relies on range sensor information for surface topology measurement. The effectiveness of the proposed method is verified via Webots simulation and real experiments on a full-body humanoid NAO robot.

中文翻译：

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基于脚部位置补偿的仿人运动主动平衡控制

本文开发了一种脚部定位补偿器，用于全身人形机器人在连续行走过程中恢复平衡。在线脚部位置补偿器（FPC）旨在提高两足动物步行的健壮性，该功能可以通过感官反馈在线修改预定义的脚步位置和步长。FPC根据策略梯度强化学习（PGRL）方法学习脚的放置参数。此外，FPC通过重新规划步行模式和质心（CoM）的轨迹，帮助类人机器人拒绝外界干扰并恢复步行位置。还提出了上身姿势控制策略，以进一步增强类人机器人的性能，以克服强烈的外部干扰。该提议方法的优点在于它既不需要关于步行地形条件的先验信息，也不依赖于范围传感器信息来进行表面拓扑测量。验证了所提方法的有效性通过Webots模拟和真实人形NAO机器人的真实实验。