Multi-robot motion planning (MRMP) is the problem of finding collision-free paths for a set of robots in a continuous state space. The difficulty of MRMP increases with the number of robots due to the increased potential for collisions between robots. This problem is exacerbated in environments with narrow passages that robots must pass through, like warehouses. In single-robot settings, topology-guided motion planning methods have shown increased performance in these constricted environments. We adapt an existing topology-guided single-robot motion planning method to the multi-robot domain, introducing topological guidance for the composite space. We demonstrate our method's ability to efficiently plan paths in complex environments with many narrow passages, scaling to robot teams of size up to five times larger than existing methods in this class of problems. By leveraging knowledge of the topology of the environment, we also find higher quality solutions than other methods.
翻译:多机器人运动规划(MRMP)是一个在连续状态空间为一组机器人寻找无碰撞路径的问题。由于机器人之间碰撞的可能性增加,MRMP的难度随着机器人数量的增加而增加。在机器人必须经过的狭小通道环境中,这个问题就更加严重了。在单机器人环境中,由地形学指导的运动规划方法显示了这些受限制环境中的更高性能。我们将现有的由地形学指导的单机器人运动规划方法适应于多机器人域,引入了复合空间的地形学指导。我们展示了我们的方法在复杂环境中以许多狭小通道有效规划路径的能力,将规模扩大到比目前这类问题中现有方法大5倍的机器人团队。我们通过利用环境地形学知识,还找到了比其他方法更高质量的解决方案。