在基于合作合规控制的多机器人精密组装中获得技能框架
Xiaogang Song1, Peng Xu1, Wenfu Xu1
1School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, PR China; Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics, Harbin Institute of Technology, Shenzhen 518055, PR China.
ISA transactions
|October 18, 2024
概括
这项研究引入了多机器人组装的新框架,提高了复杂,紧密结合的任务的学习效率. 它能够高精度的机器人组装,尽管干扰和没有事先的知识.
科学领域:
- 机器人和自动化 机器人和自动化
- 制造业 工程 制造工程
- 人工智能的人工智能
背景情况:
- 高精度机器人组装在制造业中至关重要,但受到干扰的挑战.
- 现有的研究主要涉及单一或弱合的多机器人系统.
- 紧密合的多机器人组件具有显著的不确定性是未被充分探索的.
研究的目的:
- 为复杂,紧密结合的多机器人组装任务提出一个高效的技能获取框架.
- 为了提高机器人组装系统的学习效率.
- 为了应对合作机器人组装中不确定的干扰所带来的挑战.
主要方法:
- 集成双环合力位置控制 (DLCFPC) 算法,用于同时控制运动和力.
- 实施并行技能学习算法以加快技能获取.
- 在框架内包括碰撞检测机制.
主要成果:
- 拟议的框架使多机器人系统能够实现高精度组装.
- 在合作任务中表现出对各种干扰的强度.
- 成功执行复杂的任务,如没有事先知识的插孔组装.
结论:
- 开发的框架显著提高了挑战机器人组装的学习效率.
- 它为面对不确定性的紧密合的多机器人系统提供了强大的解决方案.
- 这种方法在复杂的制造场景中促进了高精度合作装配.
相关概念视频
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