Multi-robot systems research: a data-driven trend analysis

Amorim Marques, J.V., Lorente, M.-T. and Gross, R. orcid.org/0000-0003-1826-1375 (2024) Multi-robot systems research: a data-driven trend analysis. In: Siciliano, B. and Khatib, O., (eds.) Distributed Autonomous Robotic Systems. DARS 22. 16th International Symposium on Distributed Autonomous Robotic Systems 2022 (DARS 2022), 28-30 Nov 2022, Montbéliard, France. Springer Tracts in Advanced Robotics, 28 . Springer , pp. 537-549. ISBN 978-3-031-51496-8

Abstract

Metadata

Item Type: Proceedings Paper
Authors/Creators:
Editors:
  • Siciliano, B.
  • Khatib, O.
Copyright, Publisher and Additional Information:

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG. This is an author-produced version of a paper subsequently published in Distributed Autonomous Robotic Systems. Uploaded in accordance with the publisher's self-archiving policy.
Dates:
  • Published: 1 February 2024
  • Published (online): 1 February 2024
  • Accepted: 10 September 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Funding Information:
Funder
Grant number
DEFENCE SCIENCE AND TECHNOLOGY LABORATORY
DSTLX-1000142846
Depositing User: Symplectic Sheffield
Date Deposited: 30 Jun 2023 08:40
Last Modified: 01 Feb 2025 01:13
Status: Published
Publisher: Springer
Series Name: Springer Tracts in Advanced Robotics
Refereed: Yes
Identification Number: 10.1007/978-3-031-51497-5_38
Related URLs:
Open Archives Initiative ID (OAI ID):

Export

Statistics


CORE (COnnecting REpositories)