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New PS-MAPF algorithm tackles complex multi-agent path finding in automated systems

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced Pivot-and-Station Multi-Agent Path Finding (PS-MAPF), a new variant of Multi-Agent Path Finding designed for automated high-density storage systems. This variant requires a subset of agents to visit interchangeable pivots before all agents terminate at anonymous stations. The study fully characterizes the solvability of PS-MAPF instances, indicating that all instances on 2-edge-connected graphs are solvable, and provides a condition for solvability on arbitrary connected graphs. Furthermore, the research proves that minimizing station-makespan or station-flowtime is NP-hard even with a single pivot and presents three algorithms, including Pivot-Prioritized Planning (PPP), which significantly outperforms a baseline in solving benchmark instances. AI

IMPACT Introduces a new algorithmic framework for optimizing complex multi-agent coordination in automated systems.

RANK_REASON This is a research paper detailing a new algorithm and theoretical findings in a subfield of AI. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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

New PS-MAPF algorithm tackles complex multi-agent path finding in automated systems

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This is a research paper detailing a new algorithm and theoretical findings in a subfield of AI. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Andrea Di Nezza, Mihir Patel, Fabio Fagnani, Sara Bernardini ·

    Pivot-and-Station Multi-Agent Path Finding: Solvability, Complexity, and Algorithms

    arXiv:2608.24585v1 Announce Type: new Abstract: Automated high-density storage systems (warehouses, robotic parking, plant logistics, etc.) require fleets of agents to move through scarce task-critical resources and then park without obstructing future operations. We introduce Pi…

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