技术和方法优化用于在轮腿机器人中检测脚地面接触力.
Chao Huang1, Meng Hong1, Yaodong Wang1
1Hubei Provincial Engineering Research Center of Robotics & Intelligent Manufacturing, Wuhan University of Technology, Wuhan 430070, China.
Sensors (Basel, Switzerland)
|July 12, 2025
概括
这项研究引入了一种先进的方法,用于轮腿机器人准确检测脚与地面的接触力. 这提高了机器人的稳定性和在具有挑战性的地形上进行导航.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 机械工程 机械工程
- 传感器技术 传感器技术
背景情况:
- 带轮腿的机器人通过合并带轮和带腿的机器人提供了更好的地形适应性.
- 对这些机器人来说,准确地感知脚与地面的接触力至关重要,但具有挑战性,特别是在灵活的轮胎与地面相互作用方面.
- 现有的方法难以准确估计接触位置和3D力.
研究的目的:
- 开发一个强大的脚与地面接触状态检测和优化技术,用于轮腿机器人.
- 在动态和灵活的接触场景中提高3D接触力估计的准确性.
- 增强机器人在复杂环境中运行的稳定接触感知和运动决策.
主要方法:
- 利用有限元分析 (FEA) 来模拟应变分布和全球灵敏度分析 (GSA) 来实现最佳的PVDF传感器放置.
- 开发了一个定制的实验平台,在可变的步态条件下收集动态联系数据.
- 采用高斯过程回归 (GPR) 和人工神经网络 (ANN) 模型来预测来自传感器数据的3D接触力.
主要成果:
- 经过实验验证,优化了PVDF传感器的位置.
- GPR和ANN模型准确地预测了动态3D接触力,达到8.04%的正常化根平均平方误差 (NRMSE).
- 这些模型展示了可靠的可重复性和对新输入的概括能力.
结论:
- 拟议的多传感器融合和智能建模方法显著提高了轮腿机器人脚与地面接触力估计的准确性.
- 这种技术为稳定的接触感知和复杂地形中的自适应运动控制提供了可靠的基础.
- 这些发现为推进自主轮腿机器人的能力提供了宝贵的技术支持.
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