基于稀疏A*算法与文化算法的无人机动态航迹规划

doi:10.3969/j.issn.0255-8297.2017.01.014

应用科学学报 ›› 2017, Vol. 35 ›› Issue (1): 128-138.doi: 10.3969/j.issn.0255-8297.2017.01.014

• 计算机科学与应用 • 上一篇

基于稀疏A*算法与文化算法的无人机动态航迹规划

李军华, 刘群芳

南昌航空大学信息工程学院, 南昌 330063

收稿日期:2016-01-08 修回日期:2016-08-04 出版日期:2017-01-30 发布日期:2017-01-30
作者简介:李军华,博士,副教授,研究方向:进化算法、不确定优化,E-mail:jhlee126@126.com.
基金资助:
国家自然科学基金（No.61440049）；江西省自然科学基金（No.20161BAB202038）资助

Dynamic Path Planning of Unmanned Aerial Vehicle Based on Sparse A*Algorithm and Cultural Algorithm

LI Jun-hua, LIU Qun-fang

School of Information Engineering, Nangchang Hangkong University, Nanchang 330063, China

Received:2016-01-08 Revised:2016-08-04 Online:2017-01-30 Published:2017-01-30

摘要/Abstract

摘要：

针对无人机动态航迹规划问题，结合数字地形和天气等信息建立全数字概率地图，采取先离线静态全局规划后在线实时动态规划的两级分层规划方法，基于稀疏A^*算法与文化算法实现了无人机动态航迹规划，改善了稀疏A^*算法的绕径问题，提高了航迹的可靠性和实时性.

关键词: 概率地图, 稀疏A*算法, 航迹规划, 文化算法

Abstract:

For dynamic path planning of unmanned aerial vehicle (UAV), we combine digital terrain, weather information, and other data to establish a full digital probability map.We then use a two level hierarchical planning method that includes ofine static planning and online real-time dynamic planning to realize dynamic path planning of UAV.The method is based on the sparse A^* algorithm and cultural algorithm (CA).It solves the winding problem of sparse A^* algorithm and improves reliability and real-time performance of tracking.

Key words: path planning, sparse A*algorithm, culture algorithm, probability map

中图分类号:

TP301.6

李军华, 刘群芳. 基于稀疏A*算法与文化算法的无人机动态航迹规划[J]. 应用科学学报, 2017, 35(1): 128-138.

LI Jun-hua, LIU Qun-fang. Dynamic Path Planning of Unmanned Aerial Vehicle Based on Sparse A*Algorithm and Cultural Algorithm[J]. Journal of Applied Sciences, 2017, 35(1): 128-138.

参考文献

[1] 牟衔臣,谢东来,闫威,聂晶,李想. 基于遗传算法航路规划TSP问题的研究[J]. 系统仿真学报,2013, 25(S):86-89. Mou X C, Xie D L, Yan W, Nie J, Li X. Research of theroute planning TSP problem based on the genetic algorithm[J]. Journal of System Simulation, 2013, 25(S):86-89. (in Chinese)
[2] Cui C, Wang N, Chen J. Improved ant colony optimization algorithm for UAV path planning[C]//IEEE International Conference on Software Engineering and Service Science, 2014:291- 295.
[3] Zhang Q, Shao Z H, Ping Y S, LeongY K, Hiotl M. An improved heuristic algorithm for UAV path planning in 3D environment[C]//International Conference on Intelligent Human-Machine Systems and Cybernetics, 2010:258-260.
[4] Szczerba R J. Robust algorithm for real-time route planning[J]. IEEE Transactions on Aerospace and Electronic Systems, 2000, 36(3):869-878.
[5] 占伟伟,王伟,陈能成,王超. 一种利用改进A^*算法的无人机航迹规划[J]. 武汉大学学报(信息科学版),2015, 40(3):315-320. Zhang W W, Wang W, Chen N C, Wang C. Path planning strategies for UAV based on improved A^* algorithm[J]. Journal of Geomatics and Information Science of Wuhan University, 2015, 40(3):315-320. (in Chinese)
[6] 齐仲纪,刘漫丹. 文化算法研究[J]. 计算机技术与发展,2008, 5(1):26-30. Qi Z J, Liu M D. Research on cultural algorithm[J]. Journal of Computer Technology and Development, 2008, 5(1):26-30. (in Chinese)
[7] 刘振峰,谢洪森,危水根. 基于文化蚁群算法的三维飞行器航路规划[J]. 计算机仿真,2013, 30(5):99-103. Liu Z F, Xie H S, Wei S G. Aircraft 3D route planning based on culture-ant algorithm[J]. Journal of Computer Simulation, 2013, 30(5):99-103. (in Chinese)
[8] 黎明,尹笑园,陈昊. 元胞空间结构下的文化算法[J]. 应用科学学报,2014, 32(3):263-273. Li M, Yin X Y, Chen H. The cultural algorithm based on the cellular space structure[J]. Journal of Applied Sciences, 2014, 32(3):263-273. (in Chinese)
[9] 赵明,赵玲玲,苏小红,马培军,张彦航. 一种三维多UAV协同航迹规划的空间模糊文化算法[J]. 哈尔滨工业大学学报,2015, 47(10):29-34. Zhao M, Zhao L L, Su X H, Ma P J, Zhang Y H. A spatial fuzzy cultural algorithm based on the multiple UAVs cooperative path planning under the three dimensional space[J]. Journal of Harbin Institute of Technology, 2015, 47(10):29-34. (in Chinese)
[10] Wang Z, Liu L, Long T, Yu C L, Kou J X. Enhanced sparse A^* search for UAV path planning using Dubins path estimation[C]//IEEE on Chinese Control Conference, 2014:738-742.
[11] Cheng X D, Zhou D Y, Zhang R N. New method for UAV online path planning[C]//IEEE International Conference on Signal Processing, Communication and Computing, 2013:1-5.
[12] 郜晨,甄子洋,龚华军. 雷达威胁环境下的多无人机协同航迹规划[J]. 应用科学学报,2014, 32(3):287-292. Gao C, Zhen Z Y, Gong H J. Collaborative path-planning of multiple UAV in radar threatening environment[J]. Journal of Applied Sciences, 2014, 32(3):287-292. (in Chinese)
[13] 周成平,陈前洋,秦筱楲. 基于稀疏A^* 算法的三维航迹并行规划算法[J]. 华中科技大学学报(自然科学版),2005, 33(5):42-45. Zhou C P, Chen Q Y, Qin X W. A three-dimensional track parallel programming algorithm based on the sparse A^* algorithm[J]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2005, 33(5):42-45. (in Chinese)

基于稀疏A*算法与文化算法的无人机动态航迹规划

Dynamic Path Planning of Unmanned Aerial Vehicle Based on Sparse A*Algorithm and Cultural Algorithm

PDF

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 4

编辑推荐

Metrics

本文评价

[1]	黎明, 江乐旗, 陈昊. 具有对偶知识的文化算法[J]. 应用科学学报, 2016, 34(6): 754-767.
[2]	黎明，尹笑园，陈昊. 元胞空间结构下的文化算法[J]. 应用科学学报, 2014, 32(3): 263-273.
[3]	郜晨，甄子洋，龚华军. 雷达威胁环境下的多无人机协同航迹规划[J]. 应用科学学报, 2014, 32(3): 287-292.
[4]	李猛，王道波，柏婷婷，盛守照. 基于蚁群优化算法和人工势场的无人机航迹规划[J]. 应用科学学报, 2012, 30(2): 215-220.