Salomons, N., Kapellmann-Zafra, G. and Gross, R. orcid.org/0000-0003-1826-1375 (2016) Human management of a robotic swarm. In: Towards Autonomous Robotic Systems. Towards Autonomous Robotic Systems (TAROS 2016), June 26 - July 1, 2016, Sheffield, UK. Lecture Notes in Computer Science, 9716 . Springer International Publishing , pp. 282-287.
Abstract
This paper proposes a management algorithm that allows a human operator to organize a robotic swarm via a robot leader. When the operator requests a robot to become a leader, nearby robots suspend their activities. The operator can then request a count of the robots, and assign them into subgroups, one for each task. Once the operator releases the leader, the robots perform the tasks they were assigned to. We report a series of experiments conducted with up to 30 e-puck mobile robots. On average, the counting and allocation algorithm correctly assigns 95 % of the robots in the swarm. The time to count the number of robots increases, on average, linearly with the number of robots, provided they are arranged in random formation.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 Springer International Publishing Switzerland. This is an author produced version of a paper subsequently published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 16 Sep 2016 10:37 |
Last Modified: | 21 Mar 2018 07:12 |
Published Version: | http://dx.doi.org/10.1007/978-3-319-40379-3_29 |
Status: | Published |
Publisher: | Springer International Publishing |
Series Name: | Lecture Notes in Computer Science |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-319-40379-3_29 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:104723 |