Treffer: Collision-free robot scheduling

Title:
Collision-free robot scheduling
Contributors:
University of St Andrews.School of Computer Science
Publication Year:
2026
Collection:
University of St Andrews: Digital Research Repository
Document Type:
Fachzeitschrift article in journal/newspaper
File Description:
application/pdf
Language:
English
Relation:
Information and Computation; 331402030; 86000551149; https://hdl.handle.net/10023/33434
DOI:
10.1016/j.ic.2025.105294
Rights:
Copyright © 2025 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Accession Number:
edsbas.12BD0CF9
Database:
BASE

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The authors thank the Leverhulme Trust for funding this research via the Leverhulme Research Centre for Functional Material Design. The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Nathan Flaherty reports financial support was provided by University of Liverpool Leverhulme Research Centre for Functional Materials Design (RC-2015-036). ; In this paper, we investigate the problem of designing schedules for completing a set of tasks at fixed locations with multiple robots in a laboratory. We represent the laboratory as a graph with tasks placed on fixed vertices and robots represented as agents, with the constraint that no two robots may occupy the same vertex at any given timestep. Each schedule is partitioned into a set of timesteps, corresponding to a walk through the graph (allowing for a robot to wait at a vertex to complete a task), with each timestep taking time equal to the time for a robot to move from one vertex to another and each task taking some given number of timesteps during the completion of which a robot must stay at the vertex containing the task. The goal is to determine a set of schedules, with one schedule for each robot, minimising the number of timesteps taken by the schedule taking the greatest number of timesteps within the set of schedules. We show that this problem is NP-complete for both star graphs (for k≥2 robots), and planar graphs (for any number of robots). Finally, we provide positive results for path, cycle, and tadpole graphs, showing that we can find an optimal set of schedules for k robots completing m tasks of equal duration of a path of length n in O(kmn), O(kmn2) time, and O(k3m4n) time respectively. ; Peer reviewed