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Adaptability Control Towards Complex Ground Based on Fuzzy Logic for Humanoid Robots
IEEE Transactions on Fuzzy Systems ( IF 10.7 ) Pub Date : 4-14-2022 , DOI: 10.1109/tfuzz.2022.3167458
Chencheng Dong 1 , Zhangguo Yu 1 , Xuechao Chen 1 , Huanzhong Chen 1 , Yan Huang 1 , Qiang Huang 1
Affiliation  

Stability control for humanoid robots based on zero moment point (ZMP) control and impedance control are widespread. However, uncertain changes in the center of mass (CoM) height for ZMP control and specific regulation of the variable stiffness of impedance control have been challenging issues in previous studies. In this article, these two problems are solved by implementing fuzzy control-based regulations. First, the fuzzy ZMP controller, which regulates the feedback gains online based on the CoM height change and CoM tracking errors, is proposed. Second, we propose a fuzzy regulation law for variable stiffness, which is applied for uncertain contact situations and inspired by the pattern of human muscle stiffness. With these two methods, the ground adaptability for humanoid robots is enhanced. The proposed method is validated with experiments on a real robot platform, BHR-T.

中文翻译:


基于模糊逻辑的仿人机器人对复杂地面的适应性控制



基于零力矩点(ZMP)控制和阻抗控制的仿人机器人稳定性控制非常普遍。然而,ZMP控制的质心(CoM)高度的不确定变化和阻抗控制的可变刚度的具体调节一直是先前研究中的挑战性问题。在本文中,这两个问题通过实施基于模糊控制的调节来解决。首先,提出了基于CoM高度变化和CoM跟踪误差在线调节反馈增益的模糊ZMP控制器。其次,我们提出了一种可变刚度的模糊调节律,该定律适用于不确定的接触情况,并受到人体肌肉刚度模式的启发。通过这两种方法,增强了仿人机器人的地面适应性。所提出的方法通过真实机器人平台 BHR-T 上的实验进行了验证。
更新日期:2024-08-26
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