Journal of Engineering and Applied Sciences
Year:
2017
Volume:
12
Issue:
15
Page No.
3957 - 3960
Nautical Chart Understanding for Autonomous Surface Ship Operations
Authors :
R. DurgaSingh
References
Anand, B., M. Jayandran and V. Balasubramanian, 2011. Study of formazan derivative inhibitor used to prevent the mild steel material used in the construction of ship material. Asian J. Chem., 23: 2106-2108.
Direct Link | Benjamin, M.R., 2000. IHO Transfer Standard for Digital Hydrographic Data. Internation Hydrographic Bureau, Monaco,.
Benjamin, M.R., 2004. The interval programming model for multi-objective decision making. Master Thesis, MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, Massachusetts.
Benjamin, M.R., H. Schmidt, P.M. Newman and J.J. Leonard, 2010. Nested autonomy for unmanned marine vehicles with MOOS‐IvP. J. Field Rob., 27: 834-875.
CrossRef | Direct Link | Casalino, G., A. Turetta and E. Simetti, 2009. A three-layered architecture for real time path planning and obstacle avoidance for surveillance USVs operating in harbour fields. Proceedings of the IEEE International Conference on Oceans, May 11-14, 2009, IEEE, Bremen, Germany, ISBN:978-1-4244-2522-8, pp: 1-8.
Larson, J., M. Bruch, R. Halterman, J. Rogers and R. Webster, 2007. Advances in autonomous obstacle avoidance for unmanned surface vehicles. AUVSI Unmanned Systems North America, SPAWAR Systems Center Pacific, San Diego, California.
Newman, P., 2002. MOOS: A mission oriented operating suite. Master Thesis, Massachusetts Institute of Technology, Cambridge, Massachusetts.
Sauze, C. and M. Neal, 2010. A raycast approach to collision avoidance in sailing robots. Proceedings of the International Conference on Robotic Sailing, June 7-10, 2010, Academic Publisher, Kingston, Ontario, pp: 26-33.
Sethuramalingam, T.K. and B. Nagaraj, 2015. A soft computing approach on ship trajectory control for marine applications. ARPN. J. Eng. Appl. Sci., 10: 4281-4286.
Sethuramalingam, T.K. and B. Nagaraj, 2016. A proposed system of ship trajectory control using particle swarm optimization. Procedia Comput. Sci., 87: 294-299.
Direct Link |