Multi-Robot Local Motion Planning Using Dynamic Optimization Fabrics

S. Bakker*, L. Knödler, M. Spahn, J.W. Böhmer, J. Alonso-Mora

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)

Abstract

In this paper, we address the problem of real-time motion planning for multiple robotic manipulators that operate in close proximity. We build upon the concept of dynamic fabrics and extend them to multi-robot systems, referred to as Multi-Robot Dynamic Fabrics (MRDF). This geometric method enables a very high planning frequency for high-dimensional systems at the expense of being reactive and prone to deadlocks. To detect and resolve deadlocks, we propose Rollout Fabrics where MRDF are forward simulated in a decentralized manner. We validate the methods in simulated close-proximity pick-and-place scenarios with multiple manipulators, showing high-success rates and real-time performance. Code, video: https://github.com/tud-amr/multi-robot-fabrics
Original languageEnglish
Title of host publicationProceedings of the International Symposium on Multi-Robot and Multi-Agent Systems (MRS)
PublisherIEEE
Pages149-155
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

Publication series

Name2023 International Symposium on Multi-Robot and Multi-Agent Systems, MRS 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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