Designing Heterogeneous Robot Fleets for Task Allocation and Sequencing

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Abstract

We study the problem of selecting a fleet of robots to service spatially distributed tasks with diverse requirements within time-windows. The problem of allocating tasks to a fleet of potentially heterogeneous robots and finding an optimal sequence for each robot is known as multi-robot task assignment (MRTA). Most state-of-the-art methods focus on the problem when the fleet of robots is fixed. In contrast, we consider that we are given a set of available robot types and requested tasks, and need to assemble a fleet that optimally services the tasks while the cost of the fleet remains under a budget limit. We characterize the complexity of the problem and provide a Mixed-Integer Linear Program (MILP) formulation. Due to poor scalability of the MILP, we propose a heuristic solution based on a Large Neighbourhood Search (LNS). In simulations, we demonstrate that the proposed method requires substantially lower budgets than a greedy algorithm to service all tasks.
Original languageEnglish
Title of host publicationProceedings of the International Symposium on Multi-Robot and Multi-Agent Systems (MRS)
PublisherIEEE
Pages156-162
Number of pages7
ISBN (Print)979-8-3503-7076-8
DOIs
Publication statusPublished - 2024
EventInternational Symposium on Multi-Robot and Multi-Agent Systems (MRS) - Boston, United States
Duration: 4 Dec 20235 Dec 2023

Conference

ConferenceInternational Symposium on Multi-Robot and Multi-Agent Systems (MRS)
Country/TerritoryUnited States
CityBoston
Period4/12/235/12/23

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

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