Push Recovery Methods Based on Admittance Control Strategies for a NAO-H25 Humanoid

F. Mousavi, Mehdi Tale Masouleh, A. Kalhor, P. Ghassemi
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引用次数: 3

Abstract

This paper discusses two main investigations regarding push recovery of a NAO humanoid robot. The first part indicates the simulation results of different strategies retrieved from human behaviors, namely: Ankle, Hip, and Hip-ankle strategies. These methods are separately assessed and their efficiencies are discussed. To the end of converting torque parameter to robot’s movement with a reasonable approximation in the aforementioned strategies’ obtained models, a new approach, the so-called Virtual leg model, is introduced. The second discussion assesses the admittance control strategy, which relies on disturbances’ energy absorption. Individual control algorithms are introduced for each disturbances’ categories based on NAO’s real conditions. This paper proposes a new strategy, which investigates the influence of admittance control coefficients against external disturbances, by considering a virtual interaction between robot’s feet and the ground, and introducing a Kalman-filter-based estimator. All proposed methods are simulated in NAO-H25’s simulation environment.
基于导纳控制策略的NAO-H25人形机器人推恢复方法
本文讨论了NAO类人机器人推进回收的两项主要研究。第一部分显示了从人类行为中检索到的不同策略的仿真结果,即:Ankle、Hip和Hip- Ankle策略。对这些方法分别进行了评价,并讨论了它们的效率。为了在上述策略所得到的模型中合理逼近转矩参数对机器人运动的影响,引入了一种新的方法——虚拟腿模型。第二部分讨论了基于扰动能量吸收的导纳控制策略。根据NAO的实际情况,对每一类扰动分别引入了单独的控制算法。本文提出了一种新的策略,通过考虑机器人足部与地面之间的虚拟交互作用,并引入基于卡尔曼滤波的估计器,研究导纳控制系数对外部干扰的影响。在NAO-H25的仿真环境中对所提出的方法进行了仿真。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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