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相关论文: Revisiting the Complexity Analysis of Conflict-Bas…

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Conflict-Based Search (CBS) is a powerful algorithmic framework for optimally solving classical multi-agent path finding (MAPF) problems, where time is discretized into the time steps. Continuous-time CBS (CCBS) is a recently proposed…

人工智能 · 计算机科学 2021-03-03 Anton Andreychuk , Konstantin Yakovlev , Eli Boyarski , Roni Stern

Multi-Agent Path Finding (MAPF) is the problem of finding a collection of collision-free paths for a team of multiple agents while minimizing some global cost, such as the sum of the time travelled by all agents, or the time travelled by…

多智能体系统 · 计算机科学 2022-06-02 Jaein Lim , Panagiotis Tsiotras

Conflict-Based Search (CBS) is a widely used algorithm for solving multi-agent pathfinding (MAPF) problems optimally. The core idea of CBS is to run hierarchical search, when, on the high level the tree of solutions candidates is explored,…

人工智能 · 计算机科学 2022-09-21 Ilya Ivanashev , Anton Andreychuk , Konstantin Yakovlev

In the Multi-Agent Path Finding (MAPF) problem, the goal is to find non-colliding paths for agents in an environment, such that each agent reaches its goal from its initial location. In safety-critical applications, a human supervisor may…

人工智能 · 计算机科学 2023-03-15 Justin Kottinger , Shaull Almagor , Morteza Lahijanian

Multi-Agent Path Finding (MAPF) seeks collision-free paths for multiple agents from their respective start locations to their respective goal locations while minimizing path costs. Most existing MAPF algorithms rely on a common assumption…

人工智能 · 计算机科学 2026-03-27 Xuemian Wu , Shizhe Zhao , Zhongqiang Ren

The Meta-Agent Conflict-Based Search~(MA-CBS) is a recently proposed algorithm for the multi-agent path finding problem. The algorithm is an extension of Conflict-Based Search~(CBS), which automatically merges conflicting agents into…

人工智能 · 计算机科学 2014-10-27 David Tolpin

As industries increasingly adopt large robotic fleets, there is a pressing need for computationally efficient, practical, and optimal conflict-free path planning for multiple robots. Conflict-Based Search (CBS) is a popular method for…

机器人学 · 计算机科学 2025-01-30 Scott Fredriksson , Yifan Bai , Akshit Saradagi , George Nikolakopoulos

Multi-Agent Path Finding in Continuous Time (\mapfr) extends the classical MAPF problem by allowing agents to operate in continuous time. Conflict-Based Search with Continuous Time (CCBS) is a foundational algorithm for solving \mapfr…

多智能体系统 · 计算机科学 2025-08-29 Andy Li , Zhe Chen , Danial Harabor , Mor Vered

Multi-Agent Path Finding (MAPF) is the problem of finding collision-free paths for multiple agents from their start locations to end locations. We consider an extension to this problem, Precedence Constrained Multi-Agent Path Finding…

多智能体系统 · 计算机科学 2022-02-23 Kushal Kedia , Rajat Kumar Jenamani , Aritra Hazra , Partha Pratim Chakrabarti

Conflict-Based Search (CBS) is a popular framework for solving the Multi-Agent Path Finding problem. Some of the conflicts incur a foreseeable conflict in one or both of the children nodes when splitting on them. This paper introduces a new…

人工智能 · 计算机科学 2020-07-08 Lun Yang

This paper addresses a generalization problem of Multi-Agent Pathfinding (MAPF), called Collaborative Task Sequencing - Multi-Agent Pathfinding (CTS-MAPF), where agents must plan collision-free paths and visit a series of intermediate task…

机器人学 · 计算机科学 2025-03-27 Junkai Jiang , Ruochen Li , Yibin Yang , Yihe Chen , Yuning Wang , Shaobing Xu , Jianqiang Wang

Conflict-Based Search (CBS) is a state-of-the-art algorithm for multi-agent path finding. At the high level, CBS repeatedly detects conflicts and resolves one of them by splitting the current problem into two subproblems. Previous work…

人工智能 · 计算机科学 2020-12-14 Taoan Huang , Bistra Dilkina , Sven Koenig

We present an algorithm for finding optimal paths for multiple stochastic agents in a graph to reach their destinations with a user-specified maximum pairwise collision probability. Our algorithm, called STT-CBS, uses Conflict-Based Search…

机器人学 · 计算机科学 2021-09-01 Oriana Peltzer , Kyle Brown , Mac Schwager , Mykel J. Kochenderfer , Martin Sehr

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

Conventional multi-agent path planners typically compute an ensemble of paths while optimizing a single objective, such as path length. However, many applications may require multiple objectives, say fuel consumption and completion time, to…

人工智能 · 计算机科学 2022-06-23 Zhongqiang Ren , Sivakumar Rathinam , Howie Choset

We address a variant of multi-agent path finding in continuous environment (CE-MAPF), where agents move along sets of smooth curves. Collisions between agents are resolved via avoidance in the space domain. A new Continuous Environment…

多智能体系统 · 计算机科学 2024-09-18 Kristýna Janovská , Pavel Surynek

Multi-Agent Path Finding (MAPF), i.e., finding collision-free paths for multiple robots, is important for many applications where small runtimes are necessary, including the kind of automated warehouses operated by Amazon. CBS is a leading…

人工智能 · 计算机科学 2021-03-16 Jiaoyang Li , Wheeler Ruml , Sven Koenig

The Multi-Agent Path Finding (MAPF) problem entails finding collision-free paths for a set of agents, guiding them from their start to goal locations. However, MAPF does not account for several practical task-related constraints. For…

人工智能 · 计算机科学 2024-04-23 Yu Quan Chong , Jiaoyang Li , Katia Sycara

This study informs the design of future multi-agent pathfinding (MAPF) and multi-robot motion planning (MRMP) algorithms by guiding choices based on constraint classification for constraint-based search algorithms. We categorize constraints…

机器人学 · 计算机科学 2025-11-25 Hannah Lee , James D. Motes , Marco Morales , Nancy M. Amato

We study a variant of the multi-agent path finding problem (MAPF) in which agents are required to remain connected to each other and to a designated base. This problem has applications in search and rescue missions where the entire…

人工智能 · 计算机科学 2020-06-08 Arthur Queffelec , Ocan Sankur , François Schwarzentruber
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