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最佳路径规划算法与内置的速度分析,用于协作机器人
Rafal Szczepanski1, Krystian Erwinski1, Mateusz Tejer1
1Department of Automatics and Measurement Systems, Institute of Engineering and Technology, Faculty of Physics Astronomy and Informatics, Nicolaus Copernicus University, Wilenska 7, 87-100 Torun, Poland.
本研究介绍了一种用于协作机器人的新型路径规划方法,优化生产周期. 这种方法在涉及微妙或充满液体的物品的任务中显著减少了循环时间.
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
- 优化算法 优化算法
背景情况:
- 路径规划对于高效的机器人操作至关重要,特别是在制造业.
- 现有的方法可能无法充分解决复杂任务的时间优化和流性.
- 协作机器人需要先进的规划,以确保安全高效的人机交互.
研究的目的:
- 为协作机器人开发一个时间最优,流,无碰撞的路径规划方法.
- 为了提高生产周期的效率,涉及到微妙的物品操作.
- 为了尽量减少执行时间,同时尊重机器人运动约束.
主要方法:
- 利用一种以自然为灵感的优化算法来生成B线路径.
- 开发了一种用于B-spline轨迹的速度分析算法.
- 应用了该方法来优化合作机器人的选择和放置过程.
主要成果:
- 与点对点移动相比,拟议的路径规划算法减少了11.28%的生产周期时间.
- 与具有相同运动约束的RRT*算法相比,实现了57.5%的循环时间缩短.
- 通过模拟和实验验证,通过模拟和实验验证,显著提高了流性和效率.
结论:
- 拟议的方法为协作机器人的路径规划提供了一种优越的方法,特别是对于需要精度和速度的任务.
- 优化大大减少了生产周期时间,提高了整体制造效率.
- 实验验证证证实了开发算法的实际适用性和有效性.
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