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http://dx.doi.org/10.1515/ijnaoe-2015-0007

Path planning on satellite images for unmanned surface vehicles  

Yang, Joe-Ming (Department of Systems and Naval Mechatronic Engineering, National Cheng Kung University Tainan)
Tseng, Chien-Ming (Department of Electrical Engineering and Computer Science, Masdar Institute)
Tseng, P.S. (Department of Systems and Naval Mechatronic Engineering, National Cheng Kung University Tainan)
Publication Information
International Journal of Naval Architecture and Ocean Engineering / v.7, no.1, 2015 , pp. 87-99 More about this Journal
Abstract
In recent years, the development of autonomous surface vehicles has been a field of increasing research interest. There are two major areas in this field: control theory and path planning. This study focuses on path planning, and two objectives are discussed: path planning for Unmanned Surface Vehicles (USVs) and implementation of path planning in a real map. In this paper, satellite thermal images are converted into binary images which are used as the maps for the Finite Angle $A^*$ algorithm ($FAA^*$), an advanced $A^*$ algorithm that is used to determine safer and suboptimal paths for USVs. To plan a collision-free path, the algorithm proposed in this article considers the dimensions of surface vehicles. Furthermore, the turning ability of a surface vehicle is also considered, and a constraint condition is introduced to improve the quality of the path planning algorithm, which makes the traveled path smoother. This study also shows a path planning experiment performed on a real satellite thermal image, and the path planning results can be used by an USV.
Keywords
$A^*$ algorithm; Collision avoidance; Image analysis;
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  • Reference
1 Bibuli, M., Bruzzone, G., Caccia, M. and Lapierre, L., 2009. Path-following algorithms and experiments for an unmanned surface vehicle. Journal of Field Robotics, 26, pp.669-688.   DOI
2 Botea, A., Muller, M. and Schaeffer, J., 2004. Near optimal hierarchical path-rmding. Journal of Game Development, 1, pp.1-22.
3 Caccia, M., Bibuli, M., Bono, R. and Bruzzone, G., 2008. Basic navigation, guidance and control of an unmanned surface vehicle. Autonomous Robots, 25, pp.349-365.   DOI
4 Choset, H., 2005. Principles of robot motion: theory, algorithms, and implementations. Massachusetts: MIT Press.
5 Daniel, K., Nash, A., Koenig, S., Daniel, K. and Felner, A., 2010. Theta*: Any-angle path planning on grids. Journal of Artificial Intelligence Research, 39, pp.533-579.
6 Denny, J.F., O'Brien, T.F., Bergeron, E., Twichell, D.C., Worley, C.R., Danforth, W.W., Andrews, B.A. and Irwin, B.J., 2006. Advances in shallow-water, high-resolution sea-floor mapping; integrating an autonomous surface vessel (ASV) into near shore geophysical studies. American Geophysical Union Fall Meeting (EOS Trans. AGU), San Francisco, Calif, 11-15 December 2006, 87(52).
7 Dijkstra, E.W., 1959. A note on two problems in connection with graphs. Numerische Mathematik, 1, pp.269-271.   DOI
8 Dmitri, D., Sebastian, T., Michael, M. and James, D., 2010. Path planning for autonomous vehicles in unknown semi-structured environments. The International Journal of Robotics Research, 29(5), pp.485-501.   DOI
9 Hart, P., Nilsson, N. and Raphael, B., 1968. A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science and Cybernetics, 4, pp.l00-l07.
10 Kevin, M.P., 1998. Fuzzy control. Boston: Addison Wesley Longman, Inc.
11 Lozano-P'erez, T. and Wesley, M., 2000. An algorithm for planning collision-free paths among polyhedral obstacles. Communication of the ACM, 22, pp.560-570.
12 Murphy, R., 2000. Introduction to AIrobotics. Massachusetts: MIT Press.
13 Manley, J.E., 2008. Unrnanned surface vehicles, 15 years of development. In Proceedings of MTS/IEEE Oceans'08, Quebec City, Canada, 15 - 18 September 2008, pp.1-4.
14 Naeem, W., Irwin, G.W. and Yang, A., 2011. COLREGs-based collision avoidance strategies for unmanned surface vehicle. Mechatronics, 22, pp.669-678.
15 Patel, A., 2000. Amit's Game Programming Information. [online] Available at [Accessed 3 August 2014].
16 Steve, D. , 2012. Converting UTM to latitude and longitude (or vice versa). [online] Available at http://www.policyalrnanac.org/games/aStarTutorial.htm [Accessed 3 August 2014].
17 Patrick Lester, 2005. A * path finding for beginners. [online] Available at [Accessed 3 August 2014]
18 Snyder, J.P., 1987. Map projections - a working manual. Available online: Geological Survey (U.S.). [online] Available at [Accessed 3 August 2014]
19 Steimle, E., Murphy, R., Lindemuth, M. and Hall, M., 2009. Unrnanned marine vehicle use at hurricanes wilma and ike. In Proceedings of MTS/IEEE Oceans'09, Biloxi, MS, U.S.A., 6-29 October 2009, pp.1-6
20 Tseng, C.M., Fan, C.C. and Yang, J.M., 2012. Collision-free path planning for unrnanned surface vehicle by using advanced A * algorithm. Proceedings of the 26th Asian-Pacific Technical Exchange and Advisory Meeting on Marine Structure, Fukuoka, Japan, 3 - 6 September 2012, pp.251-256.
21 Yap, P., 2002. Grid-based path-finding. Proceedings of the Canadian Conference on Artificial Intelligence, 27 - 29 May 2002, pp.44-55.