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Symbolic Planning and Multi-Agent Path Finding in Extremely Dense Environments with Unassigned Agents

2025/08/31 by Bo Fu, Fu, Bo, Zhe Chen +10
Engineering · #93A16 93A16 #Advanced Manufacturing and Logistics Optimization #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Multiagent Systems (cs.MA) #Optimization and Packing Problems #Robotics (cs.RO) #Vehicle Routing Optimization Methods

paper · pdf · doi:10.48550/arxiv.2509.01022

openalex publication_date 2025/08/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31

Abstract

We introduce the Block Rearrangement Problem (BRaP), a challenging component of large warehouse management which involves rearranging storage blocks within dense grids to achieve a goal state. We formally define the BRaP as a graph search problem. Building on intuitions from sliding puzzle problems, we propose five search-based solution algorithms, leveraging joint configuration space search, classical planning, multi-agent pathfinding, and expert heuristics. We evaluate the five approaches empirically for plan quality and scalability. Despite the exponential relation between search space size and block number, our methods demonstrate efficiency in creating rearrangement plans for deeply buried blocks in up to 80x80 grids.

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