空间多向量和多刚体障碍回避规划,用于多机器人协调悬架系统
Xiangtang Zhao1, Zhigang Zhao1, Cheng Su1
1School of Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China.
ISA transactions
|July 15, 2025
概括
本研究引入了一种新的多机器人系统,用于避开障碍,提高复杂工业任务的效率和安全性. 拟议的方法显著减少了轨迹长度,提高了计算速度,同时防止了碰撞.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统 控制系统
- 人工智能的人工智能
背景情况:
- 多机器人协调悬架系统 (MCSS) 面临着重大挑战,包括动态中的强合,导致计算复杂性的高维状态空间,以及多固体系统的有限避障策略.
- 现有的方法在动态,非凸的环境中难以实现高效的脱和实时规划,这阻碍了MCSS在工业环境中的应用.
研究的目的:
- 为多机器人协调悬架系统 (MCSS) 开发一种有效的避障规划方法.
- 解决多刚体系统中脱,计算复杂性和碰撞预防的挑战.
- 提高MCSS的效率和可扩展性,用于工业应用,如起重任务.
主要方法:
- 在一个层次搜索和步骤优化 (HSSO) 框架内提出了望远镜金字塔配置 (TPC) 和多策略喷泉启发的算法 (MGEA).
- MGEA 结合了混乱映射初始化,Lévy 飞行,差异演化和稳定性约束来提高全球搜索能力.
- 实施了分层的合作计划,以防止电缆纠和解多机器人运动.
主要成果:
- 与基准算法相比,MGEA表现出优越的性能,实现了轨迹长度减少16.35%,最低健身水平提高18.60%.
- 观察到计算速度增加了13.74%,表明效率提高.
- 该系统在混乱的3D环境中保持零碰撞,验证了其在避开障碍物的有效性.
结论:
- 拟议的TPC和MGEA为多机器人协调悬架系统提供了高效和可扩展的解决方案,特别是用于工业升降任务.
- 该HSSO框架成功实现了多向量和多刚体避障规划.
- 这项研究为动态非凸环境中的实时规划奠定了理论基础,推动了多机器人系统领域的发展.
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