实时运动同步规划,用于使用自组织竞争神经网络对多臂机器人进行合作操纵
Hui Zhang1, Hongzhe Jin2, Mingda Ge2
1Institute of Robotics, Henan University of Technology, Zhengzhou 450001, China.
Sensors (Basel, Switzerland)
|June 10, 2023
概括
本研究介绍了多臂机器人的实时规划方法,确保协同任务的同步运动. 该方法使用自组织的神经网络来提高协作操纵效率.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 控制系统 控制系统
背景情况:
- 由于物理合和同步要求,与多臂机器人合作操纵具有挑战性.
- 现有的方法经常在实时适应和实现统一的终端效应器运动方面扎.
研究的目的:
- 为物理合的多臂机器人开发实时运动同步规划方法.
- 为了提高协作操作任务的效率和稳定性.
主要方法:
- 一个自我组织的竞争神经网络被用于自适应的收率控制.
- 定义了子基础以获得常见自由度的雅可比矩阵.
- 该方法通过使次基运动趋于总姿势误差方向来确保端效应器 (EE) 运动均性.
主要成果:
- 拟议的方法实现了多臂机器人在协作任务中的快速,同步运动.
- 系统稳定性在理论上是使用利亚普诺夫理论证明的.
- 模拟和实验验证了该方法对对称和非对称合作操纵的可行性.
结论:
- 开发的动力同步规划方法有效地解决了多臂机器人协作中的实时同步挑战.
- 该方法在各种合作操纵场景中显示出稳定性和适用性.
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