Abstract 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 …

Abstract Multi-Agent Path Finding (MAPF) is the problem of planning collision-free paths for
multiple agents in a shared environment. In this paper, we propose a novel algorithm MAPF …

Abstract Multi-Agent Pathfinding (MAPF) is the problem of finding paths for multiple agents
such that each agent reaches its goal and the agents do not collide. In recent years, variants …

Abstract Multi-Agent Path Finding (MAPF) is the combinatorial problem of finding collision-
free paths for multiple agents on a graph. This paper describes MAPF-based software for …

High-tech giants and start-ups are investing in drone technologies to provide urban air
delivery service, which is expected to solve the last-mile problem and mitigate road traffic …

Effective deployment of multi-robot teams requires solving several interdependent problems
at varying levels of abstraction. Specifically, heterogeneous multi-robot systems must …

Abstract Multi-Agent Path Finding (MAPF) algorithms and their variants can find high-quality
collision-free plans for automated warehousing under simplified assumptions about the …

Conventional multiagent path finding (MAPF) problems aim to compute an ensemble of
collision-free paths for multiple agents from their respective starting locations to preallocated …

Abstract Conflict-Based Search (CBS) is a powerful algorithmic framework for optimally
solving classical multi-agent path finding (MAPF) problems, where time is discretized into …

We present a scalable and effective multi-agent safe motion planner that enables a group of
agents to move to their desired locations while avoiding collisions with obstacles and other …