UiT Autonomous Ship Program
Project Summary: The main objective in this research project is to develop the digital helmsman, ie cloned human navigator behavior, as a part of ship intelligence to operate future vessels. That will be done by analyzing real-world shipping navigation data sets collected by the UiT autonomous test vessel. The data analysis process consists of developing a deep learning based neural network to mimic human ship navigator behavior in a test vessel, supported by an onshore remote operational center. Furthermore, the cognitive ability of such neural networks under various information sources and visualization methods including human, AI, technology and regulation interactions will also be investigated to support this project.
The Four Key Pillars of the UiT Autonomous Ship Program: Human Helmsman, Digital Helmsman, Technology and Rules and Regulations and that will be evaluated under the UiT Bridge Simulator Environment, where human and AI, ie Digital Helmsman, interactions in relation to ship navigation will be further studied.
The same AI, ie Digital Helmsman, will be evaluated under the UiT Autonomous Test Vessel.
- L.P. Perera, "Autonomous Ship Navigation under Deep Learning and the challenges in COLREGs," In Proceedings of the 37th International Conference on Ocean, Offshore and Arctic Engineering (OMAE 2018), Madrid, Spain, June, 2018 (OMAE2018-77672) [The Best Paper Award of the Honoring Symposium for Professor Carlos Guedes Soares on Marine Technology and Ocean Engineering - OMAE2018].
- LP Perera, " Deep Learning Towards Autonomous Ship Navigation and Possible COLREGs Failures ," Journal of Offshore Mechanics and Arctic Engineering-Transactions of The ASME., Vol. 142, no. 3, 2020, (OMAE-19-1027) 031102.
- LP Perera and B Mo, " Machine Intelligence based Data Handling Framework for Ship Energy Efficiency ," IEEE Transactions on Vehicular Technology, vol. 66, no. 10, 2017, pp. 8659-8666.
- LP Perera, V Ferrari, FP Santos, MA Hinostroza, and C Guedes Soares, " Experimental Evaluations on Ship Autonomous Navigation & Collision Avoidance by Intelligent Guidance ," IEEE Journal of Oceanic Engineering, vol. 40, no. 2, 2015, pp 374-387.
- LP Perera, P Oliveira and C Guedes Soares, " Maritime Traffic Monitoring Based on Vessel Detection, Tracking, State Estimation, and Trajectory Prediction ," IEEE Transactions of Intelligent Transportation Systems, vol 13, no 3, 2012, pp 1188-1200 .
- LP Perera, JP Carvalho and C Guedes Soares, " Intelligent ocean navigation & Fuzzy-Bayesian decision-action formulation ," IEEE Journal of Oceanic Engineering, vol 37, no 2, 2012, pp 204-219.
- B Murray and LP Perera " Deep Representation Learning-Based Vessel Trajectory Clustering for Situation Awareness in Ship Navigation ," In Proceedings of the 5th International Conference on Maritime Technology and Engineering (MARTECH 2020), Lisbon, Portugal, November, 2020.
- LP Perera and B. Murray, " Situation Awareness of Autonomous Ship Navigation in a Mixed Environment under Advanced Ship Predictor ," In Proceedings of the 38th International Conference on Ocean, Offshore and Arctic Engineering (OMAE 2019), Glasgow, Scotland, UK, June , 2019 (OMAE2019-95571).
- B. Murray and LP Perera, " A Data-Driven Approach to Vessel Trajectory Prediction for Safe Autonomous Ship Operations ," In Proceedings of the 13th International Conference on Digital Information Management (ICDIM 2018), Berlin, Germany, September, 2018, pp. 241-247.
- LP Perera and BM Batalden " Possible COLREGs Failures under Digital Helmsman of Autonomous Ships ," In Proceedings of the MTS / IEEE OCEANS '19, Marseille, France, June, 2019.
- LP Perera, "Autonomous Ship Navigation under Deep Learning and the challenges in COLREGs," In Proceedings of the 37th International Conference on Ocean, Offshore and Arctic Engineering (OMAE 2018), Madrid, Spain, June, 2018 (OMAE2018-77672) [The Best Paper Award of the Honoring Symposium for Professor Carlos Guedes Soares on Marine Technology and Ocean Engineering - OMAE2018].
Last updated: 04.04.2021 13:22