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Main Authors: Hu, Shaoli, Zhao, Shizhe, Ren, Zhongqiang
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2509.26050
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author Hu, Shaoli
Zhao, Shizhe
Ren, Zhongqiang
author_facet Hu, Shaoli
Zhao, Shizhe
Ren, Zhongqiang
contents This paper investigates Multi-Agent Path Finding Among Movable Obstacles (M-PAMO), which seeks collision-free paths for multiple agents from their start to goal locations among static and movable obstacles. M-PAMO arises in logistics and warehouses where mobile robots are among unexpected movable objects. Although Multi-Agent Path Finding (MAPF) and single-agent Path planning Among Movable Obstacles (PAMO) were both studied, M-PAMO remains under-explored. Movable obstacles lead to new fundamental challenges as the state space, which includes both agents and movable obstacles, grows exponentially with respect to the number of agents and movable obstacles. In particular, movable obstacles often closely couple agents together spatially and temporally. This paper makes a first attempt to adapt and fuse the popular Conflict-Based Search (CBS) and Prioritized Planning (PP) for MAPF, and a recent single-agent PAMO planner called PAMO*, together to address M-PAMO. We compare their performance with up to 20 agents and hundreds of movable obstacles, and show the pros and cons of these approaches.
format Preprint
id arxiv_https___arxiv_org_abs_2509_26050
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Conflict-Based Search and Prioritized Planning for Multi-Agent Path Finding Among Movable Obstacles
Hu, Shaoli
Zhao, Shizhe
Ren, Zhongqiang
Robotics
This paper investigates Multi-Agent Path Finding Among Movable Obstacles (M-PAMO), which seeks collision-free paths for multiple agents from their start to goal locations among static and movable obstacles. M-PAMO arises in logistics and warehouses where mobile robots are among unexpected movable objects. Although Multi-Agent Path Finding (MAPF) and single-agent Path planning Among Movable Obstacles (PAMO) were both studied, M-PAMO remains under-explored. Movable obstacles lead to new fundamental challenges as the state space, which includes both agents and movable obstacles, grows exponentially with respect to the number of agents and movable obstacles. In particular, movable obstacles often closely couple agents together spatially and temporally. This paper makes a first attempt to adapt and fuse the popular Conflict-Based Search (CBS) and Prioritized Planning (PP) for MAPF, and a recent single-agent PAMO planner called PAMO*, together to address M-PAMO. We compare their performance with up to 20 agents and hundreds of movable obstacles, and show the pros and cons of these approaches.
title Conflict-Based Search and Prioritized Planning for Multi-Agent Path Finding Among Movable Obstacles
topic Robotics
url https://arxiv.org/abs/2509.26050