基于虚拟运动神经系统的六足机器人自适应运动控制

doi:10.3969/j.issn.1004-132X.2025.02.014

摘要/Abstract

摘要： 模仿动物躯干的构造，搭建了六足机器人平台；提出了在线的自适应运动控制器，通过模仿人类手臂的顺应性关节运动来实现阻抗控制参数的在线学习。与现有的虚拟运动神经系统结合，使得六足机器人可在线适应行走步态和速度，以应对不同的复杂地形。自适应运动控制器可以适应不同的任务和未知的机器人动力学，使得轨迹跟踪行为更稳定。仿真模型和六足机器人实体测试结果证明，该方法可有效提高机器人的适应性。

关键词: 六足机器人, 自适应控制, 中枢神经系统, 虚拟运动网络

Abstract: A hexapod robot platform was established by emulating the structural configuration of an animal torso. An online adaptive motion controller was introduced, which achieved impedance control parameter online learning by mimicking the compliant joint motions of the human arm. Integrated with the existing virtual motoneuron system, the hexapod robot dynamically adapted walking gaits and sped online to cope with diverse complex terrains. The adaptive motion controller exhibited versatility in accommodating different tasks and unknown robot dynamics, enhancing trajectory tracking stability. Finally, through simulation models and physical testing of the hexapod robots, the results demonstrate the effectiveness of the proposed approach in enhancing the robots adaptability.

Key words: hexapod robot, adaptive control, central pattern generator(CPG), virtual motoneuron network

中图分类号:

TP242

刘春潮1, 朱雅光1, 2, 周亚婷1, 韩志刚1. 基于虚拟运动神经系统的六足机器人自适应运动控制[J]. 中国机械工程, 2025, 36(02): 315-324,332.

LIU Chunchao1, ZHU Yaguang1, 2, ZHOU Yating1, HAN Zhigang1. Adaptive Impedance Control of Hexapod Robots Based on Virtual Motoneuron System[J]. China Mechanical Engineering, 2025, 36(02): 315-324,332.

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链接本文: https://www.cmemo.org.cn/CN/10.3969/j.issn.1004-132X.2025.02.014

https://www.cmemo.org.cn/CN/Y2025/V36/I02/315

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