Pattern formation of multi-AUV systems with the optical sensor based on displacement-based formation control

Xiaomin Wang, Benoit Zerr, Héléne Thomas, Benoit Clement and Zexiao Xie

International Journal of Systems Science, 2020, vol. 51, issue 2, 348-367

Abstract: Associated with multi-autonomous underwater vehicle (AUV) systems, the optical sensors with short working range can be reconsidered, which can provide more detailed and more comprehensive descriptions of the seabed than acoustical sensors and can assist in communications among neighbouring AUVs. The typical achievable tasks for these multi-AUV systems equipped with optical sensors mainly include to study the seabed sediments, search small objects at the seabed, collect colourful biological samples, and monitor the underwater infrastructures, etc. The purpose of this research is to develop a new coordination strategy to make a fleet of AUVs build a geometrical pattern suitable for optical sensing at the seabed. This new coordination strategy includes two parts: designing a predefined pattern (a planar pyramid pattern) and proposing an associated formation control method (an improved asynchronous discrete consensus algorithm with a time-variant digraph via the displacement-based control, inspired from the fish schooling problem) to update the trajectories of AUVs in real-time and reach this pattern from a disorder distribution. Before it is tested at sea with six AUVs, the performance of this new coordination method is verified in the simulation environments constructed in Blender and Matlab respectively. The simulation results show the good convergence of this new coordination method.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2020.1716096 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tsysxx:v:51:y:2020:i:2:p:348-367

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20

DOI: 10.1080/00207721.2020.1716096

Access Statistics for this article

International Journal of Systems Science is currently edited by Visakan Kadirkamanathan

More articles in International Journal of Systems Science from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().