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Multi-objective optimization of confidence-based localization in large-scale underwater robotic swarms.

Sabra, Adham; Fung, Wai-keung; Churn, Philip

Authors

Adham Sabra

Wai-keung Fung

Philip Churn



Contributors

Nikolaus Correll
Editor

Mac Schwager
Editor

Michael Otte
Editor

Abstract

Localization in large-scale underwater swarm robotic systems has increasingly attracted research and industry communities’ attention. An optimized confidence-based localization algorithm is proposed for improving localization coverage and accuracy by promoting robots with high confidence of location estimates to references for their neighboring robots. Confidence update rules based on Bayes filters are proposed based on localization methods’ error characteristics where expected localization error is generated based on measurements such as operational depth and traveled distance. Parameters of the proposed algorithm are then optimized using the Evolutionary Multi-objective Optimization algorithm NSGA-II for localization error and trilateration utilization minimization while maximizing localization confidence and Ultra-Short Base Line utilization. Simulation studies show that a wide localization coverage can be achieved using a single Ultra-Short Base Line system and localization mean error can be reduced by over 45% when algorithm’s parameters are optimized in an underwater swarm of 100 robots.

Citation

SABRA, A., FUNG, W.-K. and CHURN, P. 2018. Multi-objective optimization of confidence-based localization in large-scale underwater robotic swarms. In Correll, N., Schwager, M. and Otte, M. (eds.) Distributed autonomous robotic systems: proceedings of the 14th International distributed autonomous robotic systems symposium 2018 (DARS 2018), 15-17 October 2018, Boulder, USA. Springer proceedings in advanced robotics, 9. Cham: Springer [online], pages 109-123. Available from: https://doi.org/10.1007/978-3-030-05816-6_8

Conference Name 14th International distributed autonomous robotic systems symposium 2018 (DARS 2018)
Conference Location Boulder, USA
Start Date Oct 15, 2018
End Date Oct 17, 2018
Acceptance Date Aug 7, 2018
Online Publication Date Jan 30, 2019
Publication Date Feb 24, 2019
Deposit Date Feb 12, 2019
Publicly Available Date Jan 31, 2020
Publisher Springer
Pages 109-123
Series Title Springer proceedings in advanced robotics
Series Number 9
Series ISSN 2511-1256
ISBN 9783030058159
DOI https://doi.org/10.1007/978-3-030-05816-6_8
Keywords Underwater swarm localization; Confidence values; Multi-objective optimization
Public URL http://hdl.handle.net/10059/3291
Related Public URLs http://hdl.handle.net/10059/3292

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