PathSync: A Multi-Agent Path Finder

This paper presents a multi-agent pathfinding system designed for industrial environments where multiple autonomous robots operate simultaneously. The system supports up to four robots and leverages the A* search algorithm to compute optimal, collision-free paths in a grid-based workspace. A key feature of the system is its ability to handle both static and dynamic obstacles, enabling real-time path re-computation when environmental changes occur. To further enhance operational efficiency, the tool includes a novel obstacle placement suggestion mechanism that strategically recommends obstacle positions to minimize the average path length across all agents. Implemented as an interactive React-based application, the tool provides a visual and intuitive simulation environment, making it a practical solution for optimizing robot coordination in factory settings. Experimental results demonstrate the system's effectiveness in improving navigation efficiency while maintaining safe and adaptive multi-agent movement.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-17
DOI
https://doi.org/10.5281/zenodo.15680406
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.00
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article

PathSync: A Multi-Agent Path Finder

Zenodo (CERN European Organization for Nuclear Research)
Robotic Path Planning Algorithms
article

PathSync: A Multi-Agent Path Finder

article en

Abstract

This paper presents a multi-agent pathfinding system designed for industrial environments where multiple autonomous robots operate simultaneously. The system supports up to four robots and leverages the A* search algorithm to compute optimal, collision-free paths in a grid-based workspace. A key feature of the system is its ability to handle both static and dynamic obstacles, enabling real-time path re-computation when environmental changes occur. To further enhance operational efficiency, the tool includes a novel obstacle placement suggestion mechanism that strategically recommends obstacle positions to minimize the average path length across all agents. Implemented as an interactive React-based application, the tool provides a visual and intuitive simulation environment, making it a practical solution for optimizing robot coordination in factory settings. Experimental results demonstrate the system's effectiveness in improving navigation efficiency while maintaining safe and adaptive multi-agent movement.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 55%
Robotic Path Planning Algorithms
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