您所在的位置: 首页 >> 期刊 >> 计算机科学与技术汇刊

计算机科学与技术汇刊

《计算机科学与技术汇刊》是IVY出版社旗下的一本关注计算机理论与技术应用发展的国际期刊,是计算机理论与现代工业技术相结合的综合性学术刊物。主要刊登有关计算机理论,及其在自然科学、工程技术、经济和社会等各领域内的最新研究进展的学术性论文和评论性文章。旨在为该领域内的专家、学者、科研人员提供一个良好的传播、分享和探讨计算机理论与技术进展的交流平台,反映学术前沿水平,促进学术交流,推进计算机理论和应用技术的发展。本刊可接收中、英文稿件。其中,中…… 【更多】 《计算机科学与技术汇刊》是IVY出版社旗下的一本关注计算机理论与技术应用发展的国际期刊,是计算机理论与现代工业技术相结合的综合性学术刊物。主要刊登有关计算机理论,及其在自然科学、工程技术、经济和社会等各领域内的最新研究进展的学术性论文和评论性文章。旨在为该领域内的专家、学者、科研人员提供一个良好的传播、分享和探讨计算机理论与技术进展的交流平台,反映学术前沿水平,促进学术交流,推进计算机理论和应用技术的发展。

本刊可接收中、英文稿件。其中,中文稿件要有详细的英文标题、作者、单位、摘要和关键词。初次投稿请作者按照稿件模板排版后在线投稿。稿件会经过严格、公正的同行评审步骤,录用的稿件首先发表在本刊的电子刊物上,然后高质量印刷发行。期刊面向全球公开征稿、发行,要求来稿均不涉密,文责自负。

ISSN Print:2327-090X

ISSN Online:2327-0918

Email:cst@ivypub.org

Website: http://www.ivypub.org/cst/

  0
  0

Paper Infomation

Study on the Hierarchical Route Planning Under the Emergent Threats

Full Text(PDF, 1958KB)

Author: Caikun Zhang, Zhongfu Xu, Ying Cheng, Danhui Sun

Abstract: Hierarchical route planning method under the emergent threats is put forward for the emergent threats in the route planning problem. First, the basic ideas and framework of hierarchical planning are put forward on the basis of constraints of route planning. Then, the primary flight corridor planning of the bacterial foraging algorithm based on Gaussian distribution estimation algorithm and secondary optimal route planning based on heuristic A * algorithm are put forward in this paper. The primary planning effectively reduces planning domain, and the secondary planning is based on the primary planning. Real-time route planning can be carried out quickly and efficiently and the emergent threats can be effective to deal with. Finally, the simulation results prove that this method is not only scientific and reasonable, it also can effectively narrow the domain range and plan the route in real-time to avoid emergent threats.

Keywords: Route Planning, Bacterial Foraging Algorithm, Gaussian Distribution Estimation Algorithm, Heuristic A* Algorithm

References:

[1] Suresh M, Ghose D. Role of information and communication in redefining unmanned aerial vehicle autonomous control levels [J]. Journal of Aerospace Engineering, 224(2): 171-197, 2010.

[2] Zheng C W, Yan P, Ding M Y. research status and trend of route planning for flying vehicles [J]. Journal of Astronautics, 28(6): 1441-1446, 2007.

[3] Tuncer A, Yildirim M. Dynamic path planning of mobile robots with improved genetic algorithm [J]. Computers & Electrical Engineering, 38(6): 1564-1572, 2012.

[4] Duan H B, Yu Y A, Zhang X Y, er al. Three-dimension path planning for UCAV using hybrid meta-heuristic ACO-DE algorithm [J]. Simulation Modeling Practice and Theory, 18(8): 1104-1115, 2010.

[5] ZHAN W W, WANG W, CHEN N C, er al. Path Planning Strategies for UAV Based on Improved A* Algorithm [J]. Geomatics and Information Science of Wuhan University, 40(3): 315-320, 2015.

[6] Lin C L, Li Y H, Aouf N. Potential field based evolutionary route planner for the control of multiple unmanned aerial vehicles [J]. Journal of Aerospace Engineering, 224(11): 1229-1242, 2010.

[7] Alidanee B, Wang H B, Landram F. A note on integer programming formulations of the real-time optimal scheduling and fight path selection of UAVs [J]. IEEE Trans. On Control Systems Technology, 17(4): 839-843, 2009.

[8] Fu X W, Li J L, Gao X G. Defense penetration path planning for UCAV based on threat neting [J]. Acta Aeronautica et Astronautica Sinica, 35(4): 1042-1052, 2014.

[9] LI M, WANG D B, SHENG S Z, et al. Multiple route planning based on particle swarm optimization and weighted k-means clustering [J]. Systems Engineering and Electronics, 34(3):512-516, 2012.

[10] Zhang X J, Guan X M, Hwang I, et al. A hybrid distributed-centralized conflict resolution approach for multi-air-craft based on cooperative co-evolutionary [J]. Science China Information Sciences, 56(12): 1-16, 2013.

[11] Yu H, Yu Z, Li W H. Multiple routes for air vehicles based on niche particle swarm optimization [J]. Journal of Northwestern Polytechnical University, 28(3): 415-420, 2010.

[12] Xu X Q, Zhu Q B. Multi-artificial fish-swarm algorithm and a rule library based dynamic collision avoidance algorithm for robot path planning in a dynamic environment [J]. Acta Electronica Sinica, 40(8): 1694-1700, 2012.

[13] LIU X L, LI R J, YANG P. Bacterial foraging optimization algorithm based on estimation of distribution [J]. Control and Decision, 26(8): 1233-1238, 2011.

[14] JIANG J G, ZHOU J W, ZHENG Y C, et al. Adaptive bacterial foraging optimization algorithm [J]. JOURNAL OF XIDIAN UNIVERSITY, 42(1): 75-81, 2015.

[15] XI Z H, LI H B, LIU H P, et al. Multiple object tracking using A* algorithm optimization [J]. J Tsinghua Univ (Sci &. Technol), 54(12): 1549-1554, 2014.

[16] XIN Y, LIANG H W, DU M B, et al. An Improved A* Algorithm for Searching Infinite Neighbourhoods [J]. ROBOT, 36(5): 627-633, 2014.

Privacy Policy | Copyright © 2011-2024 Ivy Publisher. All Rights Reserved.

Contact: customer@ivypub.org