Open Access
Volume 37, Number 1, February 2019
Page(s) 100 - 106
Published online 03 April 2019
  1. Liu Yanju, Dai Tao, Song Jianhui. Research of Path Planning Algorithm Based on Improved Artificial Potential Field[J]. Journal of Shenyang Ligong University, 2017(1): 61-65 (in Chinese) [Article] [Google Scholar]
  2. Meng Rui, Su Weijun, Lian Xiaofeng. Mobile Robot Path Planning Based on Dynamic Fuzzy Artificial Potential Field Method[J]. Computer Engineering and Design, 2010, 31(7): 1558-1561 (in Chinese) [Article] [Google Scholar]
  3. Ding Jiaru, Du Changping, Zhao Yao, et al. Path Planning Algorithm for Unmanned Aerial Vehicles Based on Improved Artificial Potential Field[J]. Journal of Computer Applications, 2016, 36(1): 287-290 (in Chinese) [Article] [Google Scholar]
  4. Zhang T, Zhu Y, Song J. Real-Time Motion Planning for Mobile Robots by Means of Artificial Potential Field Method in Unknown Environment[J]. Industrial Robot, 2013, 37(4): 384-400 [Article] [CrossRef] [Google Scholar]
  5. Li Qing, Zhang Chao, Han Caiwei, et al. Path Planning Based on Fuzzy Logic Algorithm for Mobile Robots in Dynamic Environments[J]. Journal of Central South University, 2013(suppl 2): 104-108 (in Chinese) [Article] [Google Scholar]
  6. Karim B, Zhu Q. A Fuzzy Logic Behavior Architecture Controller for a Mobile Robot Path Planning in Multi-Obstacles Environment[J]. Research Journal of Applied Sciences Engineering & Technology, 2013, 5(14): 3835-3842 [Article] [CrossRef] [Google Scholar]
  7. Li Q, Zhang C, Han C, et al. Path Planning Based on Fuzzy Logic Algorithm for Mobile Robots in Static Environment[C]//Proceedings of IEEE Conference on Control and Decision Conference, 2013: 2866-2871 [Google Scholar]
  8. Gu Chen. Application of Improved A* Algorithm in Robot Path Planning[J]. Electronic Design Engineering, 2014(19): 96-98 (in Chinese) [Article] [Google Scholar]
  9. Zhan Weiwei, Wang Wei, Chen Nengcheng, et al. Path Planning Strategies for UAV Based on Improved A* Algorithm[J]. Geomatics and Information Science of Wuhan University, 2015, 40(3): 315-320 (in Chinese) [Article] [Google Scholar]
  10. Qu Yaohong, Xiao Zibing, Yuan Dongli. An Effective Method of UAV Flight Path Planning On-Line in Wind Field Using Improved A* Searching Algorithm[J]. Journal of Northwestern Polytechnical University, 2012, 30(4): 576-581 (in Chinese) [Article][Article] [Google Scholar]
  11. Xu Xiang, Liang Ruishi, Yang Huizhi. Path Planning for Agent Based on Improved Genetic Algorithm[J]. Computer Simulation, 2014, 31(6): 357-361 (in Chinese) [Article] [Google Scholar]
  12. Kang Bing, Wang Xihui, Liu Fu. Path Planning of Searching Robot Based on Improved Ant Colony Algorithm[J]. Journal of Jilin University, 2014, 44(4): 1062-1068 (in Chinese) [Article] [Google Scholar]
  13. Liu Yang, Zhang Weiguo, Li Guangwen, Shi Jingping. A Multi-Path Planning Method for Unmanned Aerial Vehicle(UAV) in 3D Environment[J]. Journal of Northwestern Polytechnical University, 2014, 32(3): 412-416 (in Chinese) [Article] [Google Scholar]
  14. Zhao Q, Zhen Z, Chen G, et al. Path Planning of UAVs Formation Based on Improved Ant Colony Optimization Algorithm[C]//Proceedings of IEEE Conference on Guidance, Navigation and Control, 2015: 1549-1552 [Google Scholar]
  15. Lai Zhiming, Guo Gongde. Ant Colony Optimization Based on Self-Adaption Threshold for Path Planning[J]. Computer System Applications, 2014, 23(2): 113-118 (in Chinese) [Article] [Google Scholar]
  16. Li Qing, Zhang Chao, Chen Peng, et al. Improved Ant Colony Optimization Algorithm Based on Particle Swarm Optimization[J]. Control and Decision, 2013, 28(6): 873-879 (in Chinese) [Article] [Google Scholar]
  17. Fang Qun, Xu Qing. 3D Route Planning for UAV Based on Improved PSO Algorithem[J]. Journal of Northwestern Polytechnical University, 2017, 35(1): 66-73 (in Chinese) [Article] [Google Scholar]
  18. Ying Gaoyang, Zhou Shaolei, Wu Qingpo. Efficient Path Planning Algorithm in Three Dimensions for UAV[J]. Journal of Northwestern Polytechnical University, 2016, 34(4): 564-570 (in Chinese) [Article] [Google Scholar]

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