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New SC-MAPF Algorithm Enhances Continuous Multi-Agent Path Finding

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new algorithm for smooth continuous multi-agent path finding (SC-MAPF) that operates in continuous environments with agents moving along smooth curves. This novel approach integrates a high-level search algorithm (CE-CBS) with any-angle path finding for individual agent planning, ensuring agents avoid both static obstacles and each other. Experimental results indicate that this new algorithm offers advantages over existing methods like CE-CBS, RRT*-AR, and SMT-CCBS in comparable scenarios. AI

IMPACT This research could improve coordination and efficiency in multi-agent systems operating in dynamic, continuous environments.

RANK_REASON The cluster contains a research paper detailing a new algorithm for a specific problem in multi-agent path finding. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.MA (Multiagent) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New SC-MAPF Algorithm Enhances Continuous Multi-Agent Path Finding

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The cluster contains a research paper detailing a new algorithm for a specific problem in multi-agent path finding. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Pavel Surynek ·

    Local Visibility Roadmaps in Continous Multi-agent Path Finding

    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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