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The multi-agent path finding (MAPF) problem is a combinatorial search problem that aims at finding paths for multiple agents (e.g., robots) in an environment (e.g., an autonomous warehouse) such that no two agents collide with each other,…

人工智能 · 计算机科学 2021-09-20 Aysu Bogatarkan

Multi-agent pathfinding (MAPF) is concerned with planning collision-free paths for a team of agents from their start to goal locations in an environment cluttered with obstacles. Typical approaches for MAPF consider the locations of…

人工智能 · 计算机科学 2022-03-22 David Vainshtein , Kiril Solovey , Oren Salzman

The Multi-Agent Path Finding (MAPF) problem aims at finding non-conflicting paths for multiple agents from their respective sources to destinations. This problem arises in multiple real-life situations, including robot motion planning and…

多智能体系统 · 计算机科学 2026-01-16 Aditi Anand , Dildar Ali , Suman Banerjee

Multi-Agent Path Finding (MAPF) is a fundamental problem in robotics that asks us to compute collision-free paths for a team of agents, all moving across a shared map. Although many works appear on this topic, all current algorithms…

人工智能 · 计算机科学 2024-02-01 Zhe Chen , Daniel Harabor , Jiaoyang Li , Peter J. Stuckey

Multi-Agent Pathfinding (MAPF) is the problem of finding paths for multiple agents such that every agent reaches its goal and the agents do not collide. Most prior work on MAPF was on grids, assumed agents' actions have uniform duration,…

人工智能 · 计算机科学 2019-06-17 Anton Andreychuk , Konstantin Yakovlev , Dor Atzmon , Roni Stern

Multi-Agent Path Finding (MAPF) is a fundamental problem in robotics, requiring the computation of collision-free paths for multiple agents moving from their respective start to goal positions. Coordinating multiple agents in a shared…

机器人学 · 计算机科学 2024-12-25 Jinhao Liang , Jacob K. Christopher , Sven Koenig , Ferdinando Fioretto

Multi-agent path finding (MAPF) is well-studied in artificial intelligence, robotics, theoretical computer science and operations research. We discuss issues that arise when generalizing MAPF methods to real-world scenarios and four…

Deploying multi-robot systems in environments shared with dynamic and uncontrollable agents presents significant challenges, especially for large robot fleets. In such environments, individual robot operations can be delayed due to…

机器人学 · 计算机科学 2026-03-16 Lukas Heuer , Yufei Zhu , Luigi Palmieri , Andrey Rudenko , Anna Mannucci , Sven Koenig , Martin Magnusson

Multi-Agent Motion Planning (MAMP) is the problem of computing feasible paths for a set of agents given individual start and goal states. Given the hardness of MAMP, most of the research related to multi-agent systems has focused on…

机器人学 · 计算机科学 2020-03-05 Irving Solis , Read Sandström , James Motes , Nancy M. Amato

Multi-Agent Path Finding (MAPF) involves determining paths for multiple agents to travel simultaneously and collision-free through a shared area toward given goal locations. This problem is computationally complex, especially when dealing…

Multi-agent path finding (MAPF) is the problem of finding paths for multiple agents such that they do not collide. This problem manifests in numerous real-world applications such as controlling transportation robots in automated warehouses,…

人工智能 · 计算机科学 2024-06-18 Carmel Shabalin , Omri Kaduri , Roni Stern

Multi-Agent Path Finding (MAPF) is a fundamental problem in artificial intelligence and robotics, requiring the computation of collision-free paths for multiple agents navigating from their start locations to designated goals. As autonomous…

人工智能 · 计算机科学 2025-08-01 Shiyue Wang , Haozheng Xu , Yuhan Zhang , Jingran Lin , Changhong Lu , Xiangfeng Wang , Wenhao Li

Multi Agent Path Finding (MAPF) seeks the optimal set of paths for multiple agents from respective start to goal locations such that no paths conflict. We address the MAPF problem for a fleet of hybrid-fuel unmanned aerial vehicles which…

最优化与控制 · 数学 2024-03-27 Drew Scott , Satyanarayana G. Manyam , David W. Casbeer , Manish Kumar , Isaac E. Weintraub

The multi-agent path finding (MAPF) problem is a combinatorial search problem that aims at finding paths for multiple agents (e.g., robots) in an environment (e.g., an autonomous warehouse) such that no two agents collide with each other,…

人工智能 · 计算机科学 2020-08-11 Aysu Bogatarkan , Esra Erdem

Multi-Agent Path Finding (MAPF) is the problem of moving multiple agents from starts to goals without collisions. Lifelong MAPF (LMAPF) extends MAPF by continuously assigning new goals to agents. We present our winning approach to the 2023…

多智能体系统 · 计算机科学 2026-03-02 He Jiang , Yulun Zhang , Rishi Veerapaneni , Jiaoyang Li

We consider an Anonymous Multi-Agent Path-Finding (AMAPF) problem where the set of agents is confined to a graph, a set of goal vertices is given and each of these vertices has to be reached by some agent. The problem is to find an…

人工智能 · 计算机科学 2024-01-30 Zain Alabedeen Ali , Konstantin Yakovlev

Multi Agent Path Finding (MAPF) requires identification of conflict free paths for agents which could be point-sized or with dimensions. In this paper, we propose an approach for MAPF for spatially-extended agents. These find application in…

多智能体系统 · 计算机科学 2021-06-10 Shyni Thomas , M. Narasimha Murty

Multi-agent pathfinding (MAPF) is the problem of finding a set of conflict-free paths for a set of agents. Typically, the agents' moves are limited to a pre-defined graph of possible locations and allowed transitions between them, e.g. a…

人工智能 · 计算机科学 2024-09-02 Konstantin Yakovlev , Anton Andreychuk , Roni Stern

We study the multi-agent path finding problem (MAPF) for a group of agents which are allowed to move into arbitrary directions on a 2D square grid. We focus on centralized conflict resolution for independently computed plans. We propose an…

人工智能 · 计算机科学 2016-08-10 Konstantin Yakovlev , Anton Andreychuk

Multi-Agent Path Finding (MAPF) seeks collision-free paths for multiple agents from their respective starting locations to their respective goal locations while minimizing path costs. Although many MAPF algorithms were developed and can…

多智能体系统 · 计算机科学 2024-12-24 Shuai Zhou , Shizhe Zhao , Zhongqiang Ren
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