提出新型进化算法，高效实现多机器人交叉路口协同避障规划
A Hybrid Evolutionary Approach for Multi Robot Coordinated Planning at Intersections
- 用参数化网格配置空间替代传统采样，降低计算开销
- 在复杂交叉口场景中比7种方法更快完成规划且成功率更高
- 适合工厂、仓库等多机器人密集场景的实时路径规划
交叉路口的多机器人协同运动规划对道路、工厂和仓库的安全通行至关重要。虽然快速扩展随机树（RRT）算法在多机器人路径规划中广泛应用，但在大量样本点下构建图状配置空间并搜索复合张量配置空间仍存在计算成本过高的问题。本文提出一种基于进化的新型算法，结合参数化网格配置空间与离散化RRT，实现交叉路口无碰撞的多机器人规划。通过复杂交叉口场景的计算实验表明，该算法在可行性与性能上均优于七种相关方法。研究结果为优化型多机器人导航提供了新的采样与表征机制。
原文摘要 · Abstract (English)
Coordinated multi-robot motion planning at intersections is key for safe mobility in roads, factories and warehouses. The rapidly exploring random tree (RRT) algorithms are popular in multi-robot motion planning. However, generating the graph configuration space and searching in the composite tensor configuration space is computationally expensive for large number of sample points. In this paper, we propose a new evolutionary-based algorithm using a parametric lattice-based configuration and the discrete-based RRT for collision-free multi-robot planning at intersections. Our computational experiments using complex planning intersection scenarios have shown the feasibility and the superiority of the proposed algorithm compared to seven other related approaches. Our results offer new sampling and representation mechanisms to render optimization-based approaches for multi-robot navigation.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。