在气动肌肉执行器中CPG生物反射的抗干扰控制
Lina Wang1,2, Zeling Chen1, Xiaofeng Wang1
1The Institute of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China.
iScience
|November 25, 2024
概括
这项研究为气动肌肉机器人引入了生物反射机制,提高了它们的适应性. 新的控制系统提高了对冲击和阻塞力的关节稳定性,提高了机器人的强度.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 生物模拟学是一种生物模拟学.
- 控制系统 控制系统
背景情况:
- 气动肌肉驱动的机器人在保持稳定性和适应外部干扰时面临着挑战.
- 现有的控制方法往往难以对突然冲击或连续力提供快速和强大的反应.
研究的目的:
- 设计和实施用于气动肌肉驱动机器人的生物反射机制.
- 为了提高这些机器人的适应能力和强度,防止关节干扰.
- 为了减轻对关节的突然冲击和对膝关节的持续阻塞力.
主要方法:
- 开发了一种使用关节滑动模式控制的螺旋反射控制系统.
- 集成了一个深反射控制系统与RBF神经网络自适应控制和膝关节关节的Tegotae框架.
- 使用中央模式生成器 (CPG) 作为生物反射机制的基础.
主要成果:
- 轴心反射控制器有效地将关节轨道偏差在冲击干扰下降到最低.
- 深反射控制器成功地抑制了膝关节过度紧张,并适应阻塞力.
- 实验结果显示,机器人的强度和灵活性有了显著的改善.
结论:
- 拟议的生物反射机制提高了气动肌肉驱动机器人的性能.
- 生物反射原理与先进的控制策略的整合为机器人适应性提供了一个有希望的方法.
- 这项研究验证了轴和深肌反射控制器在现实世界机器人应用中的有效性.
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