Abstract Purpose of Review Planning collision-free paths for multiple robots is important for
real-world multi-robot systems and has been studied as an optimization problem on graphs …

Multi-agent pathfinding (MAPF) is a well-studied abstract model for navigation in a multi-
robot system, where every robot finds the path to its goal position without any collision. Due …

Abstract Multi-Agent Path Finding (MAPF), ie, finding collision-free paths for multiple robots,
is important for many applications where small runtimes are necessary, including the kind of …

Abstract Multi-Agent Path Finding (MAPF) is the challenging problem of computing collision-
free paths for multiple agents. Algorithms for solving MAPF can be categorized on a …

Abstract Multi-Agent Path Finding (MAPF) is a challenging combinatorial problem that asks
us to plan collision-free paths for a team of cooperative agents. In this work, we show that …

Abstract The Multi-Agent Path Finding problem aims to find a set of collision-free paths that
minimizes the total cost of all paths. The problem is extensively studied in artificial …

Abstract Conflict-Based Search (CBS) and its enhancements are among the strongest
algorithms for Multi-Agent Path Finding. Recent work introduced an admissible heuristic to …

Path finding in multi-agent systems aims to identify collision-free and cost-optimized paths
for all agents with distinct start and goal positions. It poses challenging optimization …

We consider two new classes of pairwise path symmetries which appear in the context of
Multi-Agent Path Finding (MAPF). The first of them, corridor symmetry, arises when two …

Abstract Multi-Agent Path Finding (MAPF) is the planning problem of finding collision-free
paths for a team of agents. We focus on Conflict-Based Search (CBS), a two-level tree …