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.

翻译：交叉路口的多机器人协同运动规划对于道路、工厂和仓库中的安全移动至关重要。快速探索随机树（RRT）算法在多机器人运动规划中应用广泛。然而，对于大量采样点，生成图构型空间并在复合张量构型空间中进行搜索的计算成本高昂。本文提出一种新的基于进化的算法，它结合了基于参数的网格化构型与基于离散的RRT，用于实现交叉路口的无碰撞多机器人规划。我们在复杂交叉路口规划场景中的计算实验表明，与其它七种相关方法相比，所提算法具有可行性和优越性。我们的研究结果为多机器人导航提供了新的采样与表示机制，从而支持基于优化的方法。