A review of graph-based multi-agent pathfinding solvers: From classical to beyond classical
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 …
robot system, where every robot finds the path to its goal position without any collision. Due …
Graph-based multi-robot path finding and planning
H Ma - Current Robotics Reports, 2022 - Springer
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 …
real-world multi-robot systems and has been studied as an optimization problem on graphs …
Eecbs: A bounded-suboptimal search for multi-agent path finding
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 …
is important for many applications where small runtimes are necessary, including the kind of …
Pairwise symmetry reasoning for multi-agent path finding search
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 …
us to plan collision-free paths for a team of cooperative agents. In this work, we show that …
[HTML][HTML] Priority inheritance with backtracking for iterative multi-agent path finding
Abstract In the Multi-Agent Path Finding (MAPF) problem, a set of agents moving on a graph
must reach their own respective destinations without inter-agent collisions. In practical MAPF …
must reach their own respective destinations without inter-agent collisions. In practical MAPF …
GRSTAPS: Graphically recursive simultaneous task allocation, planning, and scheduling
Effective deployment of multi-robot teams requires solving several interdependent problems
at varying levels of abstraction. Specifically, heterogeneous multi-robot systems must …
at varying levels of abstraction. Specifically, heterogeneous multi-robot systems must …
Learning team-based navigation: a review of deep reinforcement learning techniques for multi-agent pathfinding
Multi-agent pathfinding (MAPF) is a critical field in many large-scale robotic applications,
often being the fundamental step in multi-agent systems. The increasing complexity of MAPF …
often being the fundamental step in multi-agent systems. The increasing complexity of MAPF …
Iterative refinement for real-time multi-robot path planning
We study the iterative refinement of path planning for multiple robots, known as multi-agent
pathfinding (MAPF). Given a graph, agents, their initial locations, and destinations, a solution …
pathfinding (MAPF). Given a graph, agents, their initial locations, and destinations, a solution …
Multi-goal multi-agent path finding via decoupled and integrated goal vertex ordering
P Surynek - Proceedings of the AAAI Conference on Artificial …, 2021 - ojs.aaai.org
We introduce multi-goal multi agent path finding (MG-MAPF) which generalizes the standard
discrete multi-agent path finding (MAPF) problem. While the task in MAPF is to navigate …
discrete multi-agent path finding (MAPF) problem. While the task in MAPF is to navigate …
Standby-based deadlock avoidance method for multi-agent pickup and delivery tasks
T Yamauchi, Y Miyashita, T Sugawara - arXiv preprint arXiv:2201.06014, 2022 - arxiv.org
The multi-agent pickup and delivery (MAPD) problem, in which multiple agents iteratively
carry materials without collisions, has received significant attention. However, many …
carry materials without collisions, has received significant attention. However, many …