4 accepted papers
Multi-agent coordination is crucial for reliable multi-robot navigation in shared spaces such as automated warehouses. In regions of dense robot traffic, local coordination methods may fail to find a deadlock-free solution. In these scenarios, it is appropriate to let a central unit generate a globa
Multi-Agent Path Finding (MAPF) is the problem of moving a team of agents to their goal locations without collisions. In this paper, we study the lifelong variant of MAPF, where agents are constantly engaged with new goal locations, such as in large-scale automated warehouses. We propose a new frame…
Multi-agent path finding (MAPF) is a well-studied problem in artificial intelligence that can be solved quickly in practice when using simplified agent assumptions. However, real-world applications, such as warehouse automation, require physical robots to function over long time horizons without col
Recent advances in sampling-based motion planning have exploited concepts similar to those used in the heuristic graph search community, such as computing heuristic cost-to-go estimates and using state-space abstractions to derive them. Following this trend, we explore how the concept of search effo…