All Outputs (7)

Cooperative localisation in underwater robotic swarms for ocean bottom seismic imaging. (2021)
Thesis
SABRA, A. 2021. Cooperative localisation in underwater robotic swarms for ocean bottom seismic imaging. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-1358139

Spatial information must be collected alongside the data modality of interest in wide variety of sub-sea applications, such as deep sea exploration, environmental monitoring, geological and ecological research, and samples collection. Ocean-bottom se... Read More about Cooperative localisation in underwater robotic swarms for ocean bottom seismic imaging..

A fuzzy cooperative localisation framework for underwater robotic swarms. (2020)
Journal Article
SABRA, A. and FUNG, W.-K. 2020. A fuzzy cooperative localisation framework for underwater robotic swarms. Sensors [online], 20(19), article ID 5496. Available from: https://doi.org/10.3390/s20195496

This article proposes a holistic localisation framework for underwater robotic swarms to dynamically fuse multiple position estimates of an autonomous underwater vehicle while using fuzzy decision support system. A number of underwater localisation m... Read More about A fuzzy cooperative localisation framework for underwater robotic swarms..

Multi-objective optimization of confidence-based localization in large-scale underwater robotic swarms. (2018)
Presentation / Conference Contribution
SABRA, A., FUNG, W.-K. and CHURN, P. 2018. Multi-objective optimization of confidence-based localization in large-scale underwater robotic swarms. Presented at the 14th International distributed autonomous robotic systems symposium 2018 (DARS 2018), 15-17 October 2018, Boulder, USA.

Ultra-Short Base Line (USBL) is the most commonly adopted localization method in industry due to its flexibility. However, the maximum number of underwater targets that can be simultaneously localized by USBL is very limited (up to 10 using the most... Read More about Multi-objective optimization of confidence-based localization in large-scale underwater robotic swarms..

Dynamic localization plan for underwater mobile sensor nodes using fuzzy decision support system.
Presentation / Conference Contribution
SABRA, A. and FUNG, W.-K. 2017. Dynamic localization plan for underwater mobile sensor nodes using fuzzy decision support system. In Proceedings of OCEANS 2017, 18-21 September 2017, Anchorage, Alaska, USA. New York: IEEE [online], article number 8232185, pages 854-861. Available from: http://ieeexplore.ieee.org/document/8232185

Underwater mobile sensor node localization is a key enabling technology for several subsea missions. A novel scalable underwater localization scheme, called Best Suitable Localization Algorithm (BLSA), is proposed to dynamically fuse multiple positio... Read More about Dynamic localization plan for underwater mobile sensor nodes using fuzzy decision support system..

Confidence-based underwater localization scheme for large-scale mobile sensor networks.
Presentation / Conference Contribution
SABRA, A., FUNG, W.-K. and RADHAKRISHNA, P. 2018. Confidence-based underwater localization scheme for large-scale mobile sensor networks. In Proceedings of the 2018 Marine Technology Society and Institute of Electrical and Electronics Engineers (MTS/IEEE) OCEANS conference (OCEANS 2018 MTS/IEEE), 22-25 October 2018, Charleston, USA. Piscataway, NJ: IEEE [online], article ID 8604878. Available from: https://doi.org/10.1109/OCEANS.2018.8604878

The absence of Global Positioning System in underwater environment predominates in the challenges of underwater vehicles navigation or sensor nodes tracking. Localization of single or few underwater vehicles has been fostered in recent years. However... Read More about Confidence-based underwater localization scheme for large-scale mobile sensor networks..

Multi-objective optimization of confidence-based localization in large-scale underwater robotic swarms.
Presentation / Conference Contribution
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

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

Sliding mode control with disturbance estimation for underwater robot.
Presentation / Conference Contribution
MOTOI, N., HIRAYAMA, D., YOSHIMURA, F., SABRA, A. and FUNG, W.-K. 2022. Sliding mode control with disturbance estimation for underwater robot. In Proceedings of 17th IEEE (Institute of Electrical and Electronics Engineers) international conference on Advanced motion control (AMC) 2022 (AMC 2022), 18-20 February 2022, Padova, Italy: [virtual conference]. Available from: https://doi.org/10.1109/AMC51637.2022.9729280

This paper proposes a sliding mode control with a disturbance estimation for an underwater robot. The mobility performance of an underwater robot is influenced by modeling error, observation noise, and several disturbances such as ocean current and t... Read More about Sliding mode control with disturbance estimation for underwater robot..