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相关论文: Position Paper: From Multi-Agent Pathfinding to Pi…

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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, called Multi-Agent Path Finding (MAPF). This review surveys…

机器人学 · 计算机科学 2022-06-24 Hang Ma

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 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

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

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

The MAPF problem is the fundamental problem of planning paths for multiple agents, where the key constraint is that the agents will be able to follow these paths concurrently without colliding with each other. Applications of MAPF include…

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

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

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 Path Finding (MAPF) is an important optimization problem underlying the deployment of robots in automated warehouses and factories. Despite the large body of work on this topic, most approaches make heavy simplifications, both…

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 an important core problem for many new and emerging industrial applications. Many works appear on this topic each year, and a large number of substantial advancements and performance improvements have been…

人工智能 · 计算机科学 2023-05-16 Bojie Shen , Zhe Chen , Muhammad Aamir Cheema , Daniel D. Harabor , Peter J. Stuckey

In environments where many automated guided vehicles (AGVs) operate, planning efficient, collision-free paths is essential. Related research has mainly focused on environments with pre-defined passages, resulting in space inefficiency. We…

多智能体系统 · 计算机科学 2025-11-27 Hiroya Makino , Yoshihiro Ohama , Seigo Ito

Multi-agent pathfinding (MAPF) is a problem that generally requires finding collision-free paths for multiple agents in a shared environment. Solving MAPF optimally, even under restrictive assumptions, is NP-hard, yet efficient solutions…

多智能体系统 · 计算机科学 2025-04-09 Anton Andreychuk , Konstantin Yakovlev , Aleksandr Panov , Alexey Skrynnik

The Multi-Agent Path Finding (MAPF) problem aims to find collision-free paths for multiple agents while optimizing objectives such as the sum of costs or makespan. MAPF has wide applications in domains like automated warehouses,…

机器人学 · 计算机科学 2025-12-01 Jingtian Yan , Shuai Zhou , Stephen F. Smith , Jiaoyang 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

Multi-Agent Path finding (MAPF) is the problem of finding paths for a set of agents such that each agent reaches its desired destination while avoiding collisions with the other agents. This problem arises in many robotics applications,…

多智能体系统 · 计算机科学 2026-02-24 Raz Beck , Roni Stern

Multi-agent Path Finding (MAPF) is the problem of planning collision-free movements of agents so that they get from where they are to where they need to be. Commonly, agents are located on a graph and can traverse edges. This problem has…

系统与控制 · 电气工程与系统科学 2025-06-03 Alvin Combrink , Sabino Francesco Roselli , Martin Fabian

Multi-Agent Path Finding (MAPF) is a fundamental motion coordination problem arising in multi-agent systems with a wide range of applications. The problem's intractability has led to extensive research on improving the scalability of…

多智能体系统 · 计算机科学 2023-05-26 Tzvika Geft

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
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