Robust Multi-Agent Path Finding Method for Obstacles and Environmental Changes in Factory Environments.

Seihoon Park, Jinwon Lee, Geonhyeok Park, Ikhyeon Cho, Seongjoon Moon, Woojin Chung

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Seihoon ParkDepartment of Mechanical Engineering, Korea University, Seoul 02841, Republic of Korea.ORCID 0009-0003-8574-0314

Jinwon LeeDepartment of Mechanical Engineering, Korea University, Seoul 02841, Republic of Korea.ORCID 0000-0003-0695-7578

Geonhyeok ParkDepartment of Mechanical Engineering, Korea University, Seoul 02841, Republic of Korea.ORCID 0000-0003-3111-437X

Ikhyeon ChoDepartment of Mechanical Engineering, Korea University, Seoul 02841, Republic of Korea.ORCID 0000-0002-9947-493X

Seongjoon MoonDepartment of Mechanical Engineering, Korea University, Seoul 02841, Republic of Korea.ORCID 0009-0001-7995-9200

Woojin ChungDepartment of Mechanical Engineering, Korea University, Seoul 02841, Republic of Korea.

Funding

Hyundai Mobis Company, Ltd.National Research Foundation of Korea NRF-2021R1A2C2007908

6 · The paper itself

Abstract

Multi-Agent Path Finding (MAPF) is a core technology for logistics automation in factories and warehouses. Guidance-based approaches that reflect the structural properties of factory environments have been widely adopted for computational efficiency and execution feasibility. However, these approaches generally assume static environments in which predefined guidance policies remain valid. Therefore, unexpected obstacles can cause inter-robot collisions or deadlocks. To make nominal MAPF plans robust against execution uncertainty, prior studies have incorporated bounded execution delays into MAPF. A representative method is

Indexed as

delaydynamic environmentmulti-agent path findingmulti-robotobstaclerobust planninguncertainty

Identifiers

PMID42451381

DOI10.3390/s26134139

PMCPMC13363869

What OpenQuestion holds

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.