科技快速發展的年代，利用無人載具來執行各種繁瑣或危險的任務已經變成趨勢，使得各國紛紛投入不同類型的無人載具的研發，而載具在執行各種任務時，皆需要做最初的路徑規劃，而路徑規劃不能只是執行單純的最短路徑計算，其載具的運動方式也需要加入考量，如此才能規劃出避免碰撞與載具可實際行走的路徑。而本研究以改良式FAA*路徑規劃演算法於無人船實際運動情況的路徑，加入船首的限制條件以及載具的轉向能力，並以無人船的船首為當下的方向再進行路徑規劃，以此限制條件的約束考量下能規劃出比原先FAA*所規劃的路徑更滑順且務實可行。
本研究以四旋翼空拍的影像來取代衛星影像，利用四旋翼在路徑規劃所需要的區域進行空拍作業，這是因為四旋翼的空拍影像比衛星空照圖有較好的解析度且擁有較高的即時性。四旋翼是搭配Android系列的智慧手機提升為空拍載具，手機小巧且重量輕非常適合安裝於飛行載具上，另外智慧手機系統也能成為傳輸平臺來提供所無人船所需要進行導航區域的空拍影像及各種導航所需資訊。當四旋翼於不同高度空拍後，能夠利用本研究所建立的距離與解析度關係來快速取得距離與解析度的比例，此解析度被轉換出後，GPS座標轉換系統與FAA*路徑演算法就能進行計算，而求得即時路徑規劃。

Autonomous vehicles have been a popular research topic due to its versatility. One of the essential functions in autonomous vehicles is the path planning algorithm. All kinds of autonomous vehicles require path planning algorithm according to their dynamics to prevent vehicle collision.
In this study, Finite Angle A* (FAA*) algorithm is utilized to determine the optimal path for an unmanned surface vehicle. Furthermore, the turning ability of a surface vehicle and a constraint condition for ships’ dynamics are introduced to improve the quality of FAA* algorithm. Adding these two additional conditions makes the travelling path smoother and more pragmatic.
In this research, an alternative solution for using satellite image to map is proposed. The aerial images taken by quadrotor are used as the map in this research. Using aerial image provides better resolution than satellite images, and allows for real time information. An Android smartphone is utilized as a camera as well as a system platform which can transmit the data to the unmanned surface vehicle. Due to its small size and light weight, the smartphone can be mounted on the quadrotor.
In this article, the distance-resolution correlation is determined to quickly obtain the resolution of pictures when quadrotor take these pictures at different height, and by knowing the resolution of images, the GPS coordinates in the image can be calculated and real-time path planning can be obtained.

[1] M. Achtelik, T. Zhang, K. Kuhnlenz, and M. Buss, “Visual Tracking and Control of a Quadcopter Using a Stereo Camera System and Inertial Sensors,” in Proc. of the International Conference on Mechatronics and Automation, ICMA09, pp. 2863 –2869, 2009.
[2] Choset, H., Lynch, K., Hutchinson, S., Kantor, G., Burgard, W., Kavraki,
L., & Thrun, S.. Principles of Robot Motion: Theory, Algorithms, and
Implementations, MIT Press, 2005.
[3] Murphy, R.. Introduction to AI Robotics. MIT Press, 2000.
[4] Patel, A. Amit’s Game Programming Information. available online
athttp://theory.stanford.edu/?amitp/GameProgramming/MapRepresentatio
ns.html, 2000.
[5] Dijkstra, E.W., “A note on two problems in connexion with graphs,”Numerische Mathematik, pp.269-271, 1959.
[6] Hart, P., Nilsson, N., & Raphael, B..A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science and Cybernetics, SCC-4(2),100–107, 1968.
[7] Hansen, E., & Zhou, R. Anytime Heuristic Search. Journal of Artificial Intelligence Research, 28, 267–297, 2007.
[8] Botea, A., Muller, M., & Schaeffer, J. Near optimal hierarchical path-finding. Journal of Game Development, 1(1), 1–22, 2004.
[9] J.M. Yang, C.M. Tseng & C.C. Fan. Collision –Free Path Planning for Unmanned Surface Vehicle by Using Advanced A* Algorithm, Journal of Taiwan Society of Naval Architects and Marine Engineers, Vol. 31, NO.4, pp.173-184, 2012.
[10] Caccia, M., Bibuli, M., Bono, R., & Bruzzone, G.. Basic navigation, guidance and control of an unmanned surface vehicle. Autonomous Robots, 25(4), 349–365,2008.
[11] Bibuli M., Bruzzone G., Caccia M., LapierreL.: "Path-following algorithms and experiments for an Unmanned Surface Vehicle', Journal of Field Robotics, published online in Wiley InterScience, Wiley Periodicals Inc., DOI 10.1002/rob.20303, 2009.
[12] Daniel, K., Nash, A., Koenig, S., Daniel, K., and Felner, A. Theta*: Any-angle path planning on grids, Journal of Artificial Intelligence Research, 39, 533–579, 2010.
[13] Dmitri Dolgov, Sebastian Thrun, Michael Montemerlo and James Diebel. Path Planning for Autonomous Vehicles in Unknown Semi-structured Environments, The International Journal of Robotics Research, 29, No. 5, 485–501, 2010.
[14] Charnes, A.; Frome, E. L.; Yu, P. L. (1976). "The Equivalence of Generalized Least Squares and Maximum Likelihood Estimates in the Exponential Family". Journal of the American Statistical Association 71 (353): 169.
[15] Bretscher, Otto (1995). Linear Algebra With Applications (3rd ed.). Upper Saddle River, NJ: Prentice Hall.
[16] Stigler, Stephen M. (1981). "Gauss and the Invention of Least Squares". Ann. Statist. 9 (3): 465–474.
[17] National Oceanic and Atmospheric Administration. Earth's Magnetic Field Calculators. available online at http://www.ngdc.noaa.gov/geomag/magfield.shtml, 2012.
[18] Drake, S.P., DSTO Electronics and Surveillance Research Laboratory. Converting GPS Coordinates ( ) to Navigation Coordinates (ENU) (DSTO No. DSTO-TN-0432). Retrieved from http://www.dsto.defence.gov.au/corporate/reports/DSTO-TN-0432.pdf, 2002.
[19] Steve D. Converting UTM to Latitude and Longitude (Or Vice Versa). available online at http://www.uwgb.edu/dutchs/UsefulData/UTMFormulas.htm, 2012.
[20] L. Heng, L. Meier, P. Tanskanen and M. Pollefeys. –Autonomous Obstacle Avoidance and Maneuvering on a Vision-Guided MAV Using on-Board Processing. proceedings of International Conference on Robotics and Automation, 2011.
[21] L. Meier, P. Tanskanen, L. Heng, G. Lee, F. Fraundorfer, and M. Pollefeys, “PIXHAWK: A Micro Aerial Vehicle Design for Autonomous Flight Using Onboard Computer Vision,” Autonomous Robots, pp. 1–19, 2012.
[22] F. Fraundorfer, L. Heng, D. Honegger, G. H. Lee, L. Meier, P. Tanskanen, and M. Pollefeys, “Vision-Based Autonomous Mapping and Exploration Using a Quadrotor MAV,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , pp. 4557–4564, 2012.
[23] Yang, J. M., Tseng, C. M., and Tseng, P. S. Path Planning on Satellite Images for Unmanned Surface Vehicle, Journal of Naval Architecture and Ocean Engineering, Vol.7 No.1, pp.87-99, 2015.