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Path Planning for Quadrotor UAV in 3D Environment
|關鍵字:||無人飛行載具;UAV;路徑規劃;快速擴張隨機樹;A*演算法;貝茲曲線;path planning;rapidly-exploring random tree;A-star algorithm;Bezier curve||出版社:||電機工程學系所||引用:|| A. K. Cooke, E.W.H. Fitzpatrick, “Helicopter test and evaluation,” Oxford University Blackwell Science, 2002.  C. Mary, L. C. Totu, and S. K. Koldbak,“Modelling and control of autonomous quad-Rotor,” AALBORG University, 2010.  M. G. Park, J. H. Jeon, and M. C. Lee, “Obstacle avoidance for mobile robots using artificial potential field approach with simulated annealing,” in Proceeding of IEEE International Symposium on Industrial Electronics, Pusan, Korea, pp.1530-1535, 2001.  J. Guldner and V. I. Utlun, “Sliding mode control for gradient tracking and robot navigation using artificial potential fields,” in IEEE Transaction on Robotics and Automation, vol. 11, pp. 247-254,Apr 1995.  H. Haddad, M. Khatib, S. Lacroix and R. Chatila., “Reactive navigation in outdoor environments using potential fields,” in Proceeding of IEEE International Conference on Robotics and Automation, Lewen, Belgium, Vol. 2, pp. 1232-1237,1998.  P. E. Hart, N. J. Nilsson, and B. Raphael, “A formal basis for the heuristic determination of minimum cost paths,” in IEEE Transactions on Systems Science and Cybernetics, SSC4 (2), vol. 4, pp 100–107, 1968.  R. Bellman, “Dynamic Programming,” Princeton University Press, Princeton, NJ,1957.  L. Doitsidis, , K. P. Valavanis, N.C. Tsourveloudis, and M. Kontitsis, “A framework for fuzzy logic based UAV navigation and control,” in Proceedings of the International Conference on Robotics Automation, vol. 4, pp. 4041-4046, 2004.  S. Kurnaz, O. Cetin, and O. Kaynak, "Fuzzy logic based approach to design of flight control and navigation tasks for autonomous unmanned aerial vehicles”, Journal of Intelligent & Robotic Systems, Vol. 54, pp. 229-244, March 2009.  B. Francesco, P. Lorenzo, I. Mario, "Waypoint-based fuzzy guidance for unmanned aircraft a new approach," AIAA Guidance, Navigation and Control Conference and Exhibit, 2002.  S. Tai, J. Steven, and G. Andrew, "UAV cooperative multiple task assignments using genetic algorithms," In proceeding of American Control Conference, Porland, USA, June 8-10, 2005.  K. Ashenayi and R. L. Wainwright, “Genetic algorithms for autonomous robot navigation,” IEEE Instrumentation & Measurement Magazine, vol. 10 pp.26-31, 2007.  S. Karaman and E. Frazzoli. “Incremental sampling-based algorithms for optimal motion planning”, RSS  S. M. LaValle and J. J. Kuffner, “Randomized kinodynamic planning,” IEEE International Conference on Robotics and Automation, vol. 1, pp.473-479, 1999. , May, 2010.  S. M. LaValle and J. J. Kuffner, “Rapidly-exploring random trees: Progress and prospects,” Algorithmic and Computational Robotics: New Directions, pp. 293–308, 2001.  D. Ferguson and A. Stentz. “Anytime RRTs,” In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS),pp. 5369-5375, 2006.  M. Barbehenn, “A note on the complexity of Dijkstra''s algorithm for graphs with weighted vertices,” in IEEE Transactions on Computers,Vol. 47, pp. 263, 1998.  L. Byunghee , K. Kabil “Path planning algorithm using the particle swarm optimization and the improved Dijkstra algorithm” vol. 2, pp. 1002-1004, 2008.  W. L. James, C. W. Chelsea, “A best-first search algorithm guided by a set-valued heuristic,” in IEEE Transactions on Systems, Man and Cybernetics, vol. 25, pp. 1097-1101, 1995.  W. Y. Chang, F. B. Hsiao, and D. sheu, ”The study of flight path planning for multiple target visitations,” PhD thesis, Department of Aeronautics and Astronautics, National Cheng Kung University, 2007  L. Seunghan and B. Hyochoong, “Waypoint guidance of cooperative UAVs for intelligence, surveillance, and reconnaissance,” in IEEE International Conference on Control and Automation, pp. 291-296, 2009.  N. Sapidis, W.H. Frey, “Controlling the curvature of a quadratic bezier curve,” in Computer Aided Geometric Design ,vol. 9 pp. 85-91, 1992.  Y. Kwangjin and S. Sukkarieh, “Real-time continuous curvature path planning of UAVS in cluttered environments,” in 5th International Symposium on Mechatronics and Its Applications, pp. 1-6, 2008.  E. P. Anderson, R. W. Beard, and T.W. McLain, "Real-time dynamic trajectory smoothing for unmanned air vehicles", in IEEE Transactions on Control System Technology, vol. 13, no. 3, 2005.  P. B. Sujit, and D. Ghose, “Search using multiple UAVs with flight time constraints,” IEEE Transactions on Aerospace and Electronic Systems, published online 13 Dec. 2003; Vol. 40, No. 2, 2004, pp. 491-509.  R. Ding and Y. Zhang, “The extension of the dual De Casteljau algorithm,” in Proceedings of the Fourth International Conference on Parallel and Distributed Computing, Applications and Technologies, pp.688-692, 2003.||摘要:||
對四旋翼無人飛行器在存有障礙物的三維環境中進行飛行路徑規劃是一個困難的課題。四旋翼無人飛行器利用四個螺旋翼制動器搭配變化比傳統式無人飛行器有更佳的飛行姿態變化。本篇論文提出一種快速擴張隨機樹(RRT)演算法用以決定三維環境中的最初路徑。因為自RRT 演算法獲得的路徑不盡然是最佳解同時可能存在過多的中繼點，為了解決這個問題，我們利用四旋翼飛行器的頭向作為改良A* 演算法的成本因素，用以調整自RRT 演算法獲得的最初路徑。經由改良Ａ* 演算法修正後的路徑會是片段線性且可能存在尖銳的轉折點。我們採用貝茲曲線(Bezier curves)進一步將路徑平滑化，使之適於四旋翼無人飛行器飛行。被提出的路徑規劃方法通過各種情境都得到很好的驗證。結果展示出四旋翼飛行器在三維空間中有理想的飛行。
Path planning for quadrotor unmanned aerial vehicles (UAVs) is difficult in the three-dimensional (3D) environment with obstacles. Compared with usual UAVs, a quadrotor UAV equipped with the actuators of four propellers renders it possessing
higher mobility, i.e. it can fly toward any direction freely. Taking into consideration the specific feature and the requirement of real-time flight path planning, we first develop a rapidly exploring random tree (RRT) algorithm to determine a preliminary flight path, especially for quadrotor UAVs, in 3D space. Since the path obtained by the RRT is not necessarily optimal and excessive waypoints usually need to be refined. We further adopt headings of quadrotor UAV as the moving cost of the improved A* algorithm. The secondary path generated by the improved A-star algorithm is piecewise linear and may sometimes exhibit rugged curvature. Bezier curves are them utilized to refine the flight path obtained via the A-star algorithm making it to be applicable for real-world quadrotor UAV flight. The proposed path planning method has been well verified via a variety of scenarios. The results show satisfactory flight parts for quadrotor UAVs in 3D environment.
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