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http://dx.doi.org/10.1016/j.ijnaoe.2021.07.002

Mission planning and performance verification of an unmanned surface vehicle using a genetic algorithm  

Park, Jihoon (Department of Aerospace Engineering, Pusan National University)
Kim, Sukkeun (Department of Aerospace Engineering, Pusan National University)
Noh, Geemoon (Department of Aerospace Engineering, Pusan National University)
Kim, Hyeongmin (Department of Aerospace Engineering, Pusan National University)
Lee, Daewoo (Department of Aerospace Engineering, Pusan National University)
Lee, Inwon (Department of Naval Architecture & Ocean Engineering, Pusan National University)
Publication Information
International Journal of Naval Architecture and Ocean Engineering / v.13, no.1, 2021 , pp. 575-584 More about this Journal
Abstract
This study contains the process of developing a Mission Planning System (MPS) of an USV that can be applied in real situations and verifying them through HILS. In this study, we set the scenario of a single USV with limited operating time. Since the USV may not perform some missions due to the limited operating time, an objective function was defined to maximize the Mission Achievement Rate (MAR). We used a genetic algorithm to solve the problem model, and proposed a method using a 3-D population. The simulation showed that the probability of deriving the global optimal solution of the mission planning algorithm was 96.6% and the computation time was 1.6 s. Furthermore, USV showed it performs the mission according to the results of the MPS. We expect that the MPS developed in this study can be applied to the real environment where USV performs missions with limited time conditions.
Keywords
Unmanned surface vehicle; Vehicle routing problem; Genetic algorithm; Mission planning system; HILS;
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1 Park, H.B., Heo, J.W., Oh, G.W., 2017. The Domestic Development Strategy through International Research Review of Unmanned Surface Vehicle. SASE Fall Conference, pp. 144-145, 2017.
2 Zanoli, S.M., Astolfi, G., Bruzzone, G., Bibuli, M., Caccia, M., 2012. Application of fault detection and isolation techniques on an unmanned surface vehicle (USV). IFAC Proceed. Vols. 45 (27), 287-292.
3 Caccia, M., Bibuli, M., Bruzzone, G., Bruzzone, G., Bono, R., Spirandelli, E., 2009. Charlie, a testbed for usv research. IFAC Proceed. Vols. 42 (18), 97-102.
4 Holland, J.H., 1992. Genetic algorithms. Sci. Am. 267 (1), 66-73.   DOI
5 Pisinger, D., Ropke, S., 2007. A general heuristic for vehicle routing problems. Comput. Oper. Res. 34 (8), 2403-2435.   DOI
6 Wu, B., Wen, Y., Huang, Y., Zhu, M., 2013. Research of unmanned surface vessel (USV) path-planning algorithm based on ArcGIS. In: ICTIS 2013: Improving Multimodal Transportation Systems-Information, Safety, and Integration, pp. 2125-2134.
7 Hwang, H.G., Kim, H.W., Kim, B.S., Woo, Y.T., Shin, I.S., Shin, J.H., Choi, B.W., 2017. A development of integrated control system for platform equipments of unmanned surface vehicle (USV). J. Korea Inst. Inform. Commun. Eng. 21 (8), 1611-1618.   DOI
8 Miller, C.E., Tucker, A.W., Zemlin, R.A., 1960. Integer programming formulation of traveling salesman problems. J. ACM 7 (4), 326-329.   DOI
9 Noreen, I., Khan, A., Habib, Z., 2016. Optimal path planning using RRT* based approaches: a survey and future directions. Int. J. Adv. Comput. Sci. Appl. 7 (11), 97-107.
10 Grefenstette, J., Gopal, R., Rosmaita, B., Van Gucht, D., 1985, July. Genetic algorithms for the traveling salesman problem. In: Proceedings of the First International Conference on Genetic Algorithms and Their Applications, vol. 160. Lawrence Erlbaum, pp. 160-168. No. 168.
11 Little, J.D., Murty, K.G., Sweeney, D.W., Karel, C., 1963. An algorithm for the traveling salesman problem. Oper. Res. 11 (6), 972-989.   DOI
12 Goldberg, D.E., Lingle, R., 1985, July. ). Alleles, loci, and the traveling salesman problem. In: Proceedings of an International Conference on Genetic Algorithms and Their Applications, vol. 154. Lawrence Erlbaum, Hillsdale, NJ, pp. 154-159.