Parallel Hierarchical Composition Conflict-Based Search for Optimal Multi-Agent Pathfinding

被引：12

作者：

Lee, Hannah ^{[1
]}

Motes, James ^{[1
]}

Morales, Marco ^{[1
,2
]}

Amato, Nancy M. ^{[1
]}

机构：

[1] Univ Illinois, Dept Comp Sci, Parasol Lab, Champaign, IL 61820 USA

[2] Inst Tecnol Autonomo Mexico, Mexico City 01080, DF, Mexico

来源：

IEEE ROBOTICS AND AUTOMATION LETTERS | 2021年 / 6卷 / 04期

基金：

美国国家科学基金会;

关键词：

Multi-robot systems; path planning; parallel algorithms;

D O I：

10.1109/LRA.2021.3096476

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

In this letter, we present the following optimal multi-agent pathfinding (MAPF) algorithms: Hierarchical Composition Conflict-Based Search, Parallel Hierarchical Composition Conflict-Based Search, and Dynamic Parallel Hierarchical Composition Conflict-Based Search. MAPF is the task of finding an optimal set of valid path plans for a set of agents such that no agents collide with present obstacles or each other. The presented algorithms are an extension of Conflict-Based Search (CBS), where the MAPF problem is solved by composing and merging smaller, more easily manageable subproblems. Using the information from these subproblems, the presented algorithms can more efficiently find an optimal solution. Our three presented algorithms demonstrate improved performance for optimally solving MAPF problems consisting of many agents in crowded areas while examining fewer states when compared with CBS and its variant Improved Conflict-Based Search.

引用

页码：7001 / 7008

页数：8

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