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首页> 外文期刊>The Journal of Artificial Intelligence Research >Exploiting Subgraph Structure in Multi-Robot Path Planning
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Exploiting Subgraph Structure in Multi-Robot Path Planning

机译:在多机器人路径规划中利用子图结构

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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 conicting; we demonstrate how they can be combined into a single algorithm which outperforms either approach alone.
机译:由于每增加一个新机器人,搜索空间便会爆炸性增长,因此多机器人路径规划非常困难。完全搜索组合状态空间很快变得很棘手。在本文中,我们提出了一种新颖的抽象形式,使我们可以更有效地进行计划。这种抽象的关键是将地图分为具有入口和出口限制的已知结构子图,我们可以紧凑地表示这些子图。然后,计划就成为在较小的子图配置空间中进行的搜索。一旦找到抽象计划,就可以将其快速解析为正确的(但可能不是最优的)具体计划,而无需进一步搜索。我们证明了该技术是完善和完善的,并在实际地图上证明了其实际有效性。一个有竞争力的解决方案,即优先计划,也经过评估,显示出具有相似的性能,尽管以完整性为代价。这两种方法不一定是冲突的。我们展示了如何将它们组合成一个单独的算法,其性能优于任何一种方法。

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