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Walking Motion Generation and Neuro-Fuzzy Control with Push Recovery for Humanoid Robot

机译:仿人机器人步行运动产生和神经模糊控制及推挽恢复

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Push recovery is an essential requirement for a humanoid robot with the objective of safely performing tasks within a real dynamic environment. In this environment, the robot is susceptible to external disturbance that in some cases is inevitable, requiring push recovery strategies to avoid possible falls, damage in humans and the environment. In this paper, a novel push recovery approach to counteract disturbance from any direction and any walking phase is developed. It presents a pattern generator with the ability to be modified according to the push recovery strategy. The result is a humanoid robot that can maintain its balance in the presence of strong disturbance taking into account its magnitude and determining the best push recovery strategy. Push recovery experiments with different disturbance directions have been performed using a 20 DOF Darwin-OP robot. The adaptability and low computational cost of the whole scheme allows is incorporation into an embedded system.
机译:推动恢复是类人机器人的基本要求,其目标是在真实的动态环境中安全地执行任务。在这种环境下,机器人容易受到外部干扰的影响,在某些情况下是不可避免的,因此需要采取推挽恢复策略,以防止跌倒,人身伤害和环境破坏。在本文中,开发了一种新颖的推挽恢复方法来抵消来自任何方向和任何行走阶段的干扰。它提供了一种模式生成器,可以根据推送恢复策略进行修改。结果是仿制人形机器人可以在存在严重干扰的情况下保持平衡,并考虑其大小并确定最佳的推挽恢复策略。使用20 DOF Darwin-OP机器人进行了具有不同干扰方向的推式恢复实验。整个方案的适应性和低计算成本允许被并入嵌入式系统中。

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