English(EN) Local Visibility Roadmaps in Continous Multi-agent Path Finding

新的SC-MAPF算法增强了连续多智能体路径寻找

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-03 14:10

研究人员开发了一种用于平滑连续多智能体路径寻找（SC-MAPF）的新算法，该算法在智能体沿平滑曲线移动的连续环境中运行。这种新颖的方法将高级搜索算法（CE-CBS）与个体智能体规划的任意角度路径寻找相结合，确保智能体避免静态障碍物并相互避让。实验结果表明，在新算法在可比场景中优于CE-CBS、RRT*-AR和SMT-CCBS等现有方法。 AI

影响这项研究可以提高在动态、连续环境中运行的多智能体系统的协调性和效率。

排序理由该集群包含一篇详细介绍多智能体路径寻找特定问题新算法的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.MA (Multiagent) 阅读 →

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arXiv cs.MA (Multiagent) TIER_1 English(EN) · Pavel Surynek · 2026-11-03 14:10

持续多智能体路径寻找中的局部可见性路线图

We address the problem of smooth continuous multi-agent path finding (SC-MAPF), where agents move in a continuous environment along smooth curves in continuous time. The paths for individual agents are searched in local visibility roadmaps that consider obstacles and other agents…

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持续多智能体路径寻找中的局部可见性路线图

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