Subdimensional expansion method for multi-agent path finding with long narrow corridors
You, Haoyuan
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Permalink
https://hdl.handle.net/2142/130069
Description
Title
Subdimensional expansion method for multi-agent path finding with long narrow corridors
Author(s)
You, Haoyuan
Issue Date
2025-07-25
Director of Research (if dissertation) or Advisor (if thesis)
Driggs-Campbell, Katherine Rose
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Multi-agent path finding
Robotics
Abstract
Multi-agent path finding, a problem largely related to the field of robotics, has been proven to be an NP-Hard problem and computationally heavy. Experience-based planning method is a sample-based method that uses a pre-computed database to reduce the planning time. We propose an algorithm that extends based on a prior experience-based framework to target specifically multi-agent path planning problems with long narrow corridors. By leveraging graph homomorphism, we expand a database for doorway problems to cover corridors with various shapes and sizes. The algorithm can find solutions for MAPF problems with a consistent 60-70% higher success rate compared to multiple baselines in environments with multiple narrow corridors without sacrificing performance. The proposed algorithm shows the ability to plan the paths for about a hundred robots in congested simulated environments with and without narrow corridors within a few seconds.
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