Exploiting Subgraph Structure in Multi-Robot Path Planning
Malcolm Ross Kinsella Ryan
- 发表年份
- 2011
- 访问权限
- 开放获取
摘要
Multi-robot path planning is difficult due to the combinatorial explosion of the search space with every new robot added. Complete search of the combined state-space soon becomes intractable. In this paper we present a novel form of abstraction that allows us to plan much more efficiently. The key to this abstraction is the partitioning of the map into subgraphs of known structure with entry and exit restrictions which we can represent compactly. Planning then becomes a search in the much smaller space of subgraph configurations. Once an abstract plan is found, it can be quickly resolved into a correct (but possibly sub-optimal) concrete plan without the need for further search. We prove that this technique is sound and complete and demonstrate its practical effectiveness on a real map. A contending solution, prioritised planning, is also evaluated and shown to have similar performance albeit at the cost of completeness. The two approaches are not necessarily conflicting; we demonstrate how they can be combined into a single algorithm which outperforms either approach alone.
关键词
相关论文
基于大语言模型增强的多智能体强化学习的无人机博弈分层决策
Xinyu Dong, Bo Li, Guangyu Zhang 等 5 位作者
Aerospace Science and Technology · 2026
基于嵌入式语言模型的多机器人系统动态重构
Shokhikha Amalana Murdivien, Jongsu Park, Jumyung Um
Robotics and Computer-Integrated Manufacturing · 2026
水下残骸区域多UUV协同覆盖搜索的编队优化与避碰决策方法
Haomiao Yu, Zeyuan Zhang, Yantian Ma
Robotics and Autonomous Systems · 2026
人在回路中的群体机器人:一种用于真实土壤测绘的仿生群体方法
Petras Swissler, Mohammadali Rashidioun, Nicholas Sahu 等 6 位作者
2026