晶圆传递机器人手臂振动轨迹规划 基于灰色的优化
1School of Mechanical Engineering, Shenyang Ligong University, Shenyang 110159, China.
Sensors (Basel, Switzerland)
|February 13, 2026
概括
半导体晶圆处理机器人使用灰优化 (GGO) 来抑制振动. 这种方法通过优化轨迹以实现更快,更流的晶圆运输来提高定位精度和系统稳定性.
科学领域:
- 机器人和自动化 机器人和自动化
- 控制系统工程 控制系统工程
- 优化算法 优化算法
背景情况:
- 晶圆处理机器人在半导体制造中对于高速,精确的运输至关重要.
- 轻量级快速移动机器人的灵活部件会引起残余振动,降低准确性和稳定性.
研究的目的:
- 为处理晶圆机器人提出一种新的抑制振动轨迹规划方法.
- 为了提高半导体制造中的定位精度和系统稳定性.
主要方法:
- 利用灰优化 (GGO) 算法进行多目标轨迹规划.
- 开发了一种平衡运动时间和振动能量的多目标功能.
- 确定了S形速度配置文件的最佳切换时间点.
主要成果:
- GGO算法在基准函数上表现出了有效性和稳定性.
- 计划的轨迹在干扰下显示了可以忽略不计的位移变化.
- 实现了帕雷托最佳解决方案,平衡了运动时间和残余振动能量.
结论:
- 基于GGO的方法有效地抑制了晶圆处理机器人的振动.
- 这种方法增强了轨迹的平滑性,速度和加速控制.
- 这使得半导体制造业的定位精度和系统稳定性得到改善.
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