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Solving the Non-Crossing MAPF with CP

Authors Xiao Peng, Christine Solnon, Olivier Simonin

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Author Details

Xiao Peng
  • CITI, INRIA, INSA Lyon, F-69621, Villeurbanne, France
Christine Solnon
  • CITI, INRIA, INSA Lyon, F-69621, Villeurbanne, France
Olivier Simonin
  • CITI, INRIA, INSA Lyon, F-69621, Villeurbanne, France

Funding

This work was supported by the European Commission under the H2020 project BugWright2 (871260): Autonomous Robotic Inspection and Maintenance on Ship Hulls and Storage Tanks.

Cite AsGet BibTex

Xiao Peng, Christine Solnon, and Olivier Simonin. Solving the Non-Crossing MAPF with CP. In 27th International Conference on Principles and Practice of Constraint Programming (CP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 210, pp. 45:1-45:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/LIPIcs.CP.2021.45

Abstract

We introduce a new Multi-Agent Path Finding (MAPF) problem which is motivated by an industrial application. Given a fleet of robots that move on a workspace that may contain static obstacles, we must find paths from their current positions to a set of destinations, and the goal is to minimise the length of the longest path. The originality of our problem comes from the fact that each robot is attached with a cable to an anchor point, and that robots are not able to cross these cables. We formally define the Non-Crossing MAPF (NC-MAPF) problem and show how to compute lower and upper bounds by solving well known assignment problems. We introduce a Variable Neighbourhood Search (VNS) approach for improving the upper bound, and a Constraint Programming (CP) model for solving the problem to optimality. We experimentally evaluate these approaches on randomly generated instances.

Subject Classification

ACM Subject Classification
  • Computing methodologies
Keywords
  • Constraint Programming (CP)
  • Multi-Agent Path Finding (MAPF)
  • Assignment Problems

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