基于动力学的多功能约束识别,应用于机器人任务复制
Alex H G Overbeek1, Douwe Dresscher2, Herman van der Kooij1
1Department of Biomechanical Engineering, University of Twente, Enschede, Netherlands.
Frontiers in robotics and AI
|July 30, 2025
概括
这项研究引入了一种新的动力学方法,用于识别机器人环境约束,增强自主任务执行. 这种多功能方法在没有事先信息的情况下工作,提高了机器人在现实环境中的适应性.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 机器学习 机器学习
- 控制理论 控制理论
背景情况:
- 识别动力学约束对于机器人执行任务至关重要.
- 现有的方法往往需要特定的预先信息或测量,限制了它们的适用性.
- 对于现实世界的机器人系统,需要一种多功能,信息不可知的方法.
研究的目的:
- 为确定机器人环境约束提出一种多功能,仅基于动力学的方法.
- 为了使限制识别在没有限制模型,几何或力测量的事先知识的情况下.
- 在模拟和现实世界机器人实验中证明该方法的有效性.
主要方法:
- 使用固定在机器人或地面物体上的约束参考框架.
- 通过最小化这些框架内的笛卡尔元件中的速度规范来识别约束.
- 仅采用动力学方法,仅依赖于测量动力学.
主要成果:
- 在模拟中成功识别了12个不同的约束的几何,包括接,多面体和轮接触.
- 已经证明,随着传感器噪声的增加,准确性线性下降.
- 在机器人实验中实现了与现有文献方法相比较的任务复制性能.
结论:
- 拟议的纯动力学方法为识别机器人环境约束提供了一种多功能解决方案.
- 该方法适用于各种机器人和缺乏先前约束信息的环境,适用于日常机器人应用.
- 这种方法通过使机器人能够学习和适应环境约束来增强自主任务执行.
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