感知期望使智能软连续机器人能够同时进行自身感知和接触检测
Peiyi Wang1,2,3, Zhexin Xie2,3, Wenci Xin2,3
1School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing, China.
Nature communications
|November 18, 2024
概括
这项研究为软机器人引入了一种新的感知-动作循环,使得快速和强大的接触检测和变形源识别成为可能. 该系统准确地感知接触方向,增强机器人交互能力.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 生物仿真工程 生物仿真工程
- 控制系统 控制系统
背景情况:
- 人类大脑的感知模型是复杂的交互任务中机器人控制的关键.
- 软机器人可以利用类似的机制来加强环境交互.
- 现有的方法缺乏强大的实时感知,用于软机器人操纵.
研究的目的:
- 为软机器人提出和演示一个预期的实际感知-动作循环.
- 为了在软连续机器人中实现强大的接触检测和变形源识别.
- 在视力有限的环境中增强软机器人的交互能力.
主要方法:
- 开发了一个有传感器的软连续机器人.
- 实现了预期的实际感知-动作循环,用于实时反.
- 利用形状传感来匹配预期和实际的机器人配置.
- 在各种条件下测试了接触检测和方向感知.
主要成果:
- 实现了快速接触检测 (在0.4秒内),形状估计误差低 (1.4%).
- 成功地区分了外部和内部变形源,即使同时应用.
- 在静态和动态场景中证明了接触方向的准确感知 (误差<10°).
- 展示了自主导航和人机交互,用于学习所需的配置.
结论:
- 拟议的感知-动作循环显著改善软机器人的感知和控制.
- 这种方法使软机器人能够在复杂的环境中进行强大的交互和操纵.
- 该方法在自主导航和人机协作中具有潜在的应用.
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