一个双层重量导体-维塞克模型用于仓库中的多重AGV路径规划
Shiwei Lin1, Ang Liu1, Jianguo Wang1
1Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia.
Biomimetics (Basel, Switzerland)
|November 24, 2023
概括
本研究介绍了一种双层策略,用于在工业环境中高效的多车道规划. 该方法使用虚拟领导者和新的Weight-Leader-Vicsek模型进行实时导航和避免碰撞.
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
- 运营研究 运营研究
背景情况:
- 多重自动引导车辆 (AGV) 是工业智能的组成部分,需要高效的路径规划以实现最佳运行.
- 实时,多个AGV的稳健路径规划带来了重大的计算和效率挑战.
研究的目的:
- 为多车路线规划制定一个双层策略,确保快速计算和运营效率.
- 为了实现实时导航,并实施多个AGV的碰撞/死锁避免.
主要方法:
- 两层方法:第一层使用混合A*算法,基于组合的车辆进行虚拟领导者路径规划.
- 第二层采用了Weight-Leader-Vicsek模型,用于追随者车辆向他们的虚拟领导者导航.
- 将不同组的车辆视为动态障碍物,整合碰撞和避免死锁.
主要成果:
- 拟议的方法大大降低了计算负载,通过组装车辆的快速状态更新实现实时导航.
- 在MATLAB中的模拟验证了路径规划功能,证明了有效的多车辆协调.
- 使用定位传感器进行实验验证.
结论:
- 开发的双层策略为实时多车道路线规划提供了计算高效和有效的解决方案.
- 虚拟领导者和Weight-Leader-Vicsek模型的整合在复杂的工业环境中促进了强大的导航和安全.
- 这种方法解决了智能工业应用部署多个AGV的关键挑战.
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