References
[1]. Ge W.Y., Li P.. Secure A* algorithm for path planning of mobile robots [J/OL]. Journal of Huaqiao University
[2]. KHATIB O.Real-time obstacle avoidance for manipulatorsand mobile robots[C]//ProceedingsIEEE InternationalCon-ference on Robotics and Automation，1985;500-505.
[3]. Luo Q., Wang H. B., Cui S. J., et al. Improved artificial potential field method for autonomous mobile robot path planning [J]. Control Engineering, 2019, 26(6): 1091-1098.
[4]. Guo Lopeng. Research on path planning algorithm based on improved artificial potential field method [D]. Harbin: Harbin Institute of Technology, 2017.
[5]. Juidette H , Youlal H. Fuzzy dynamic path planning using genetic algorithms [J]. Electronics Letters ,2000,36(4);374—376.
[6]. Zhang Feizhou, Yan Lei , Fan Yuezu , et al. Optimizing dis patching of public traffic vehicles in intelligent transport system[J] . Journal of Beijing University of Aeronautics and Astronautics ,2002,28(6) ;707-710.
[7]. Yu L, Gong J, Zhang J, et al. Genetic — algorithm — based path optimization methodology for spatial decision [C]. Los Angeles : Geoinformatics , Geospatial Information Science. International Society for Optics and Photonics ,2006.
[8]. Mahjoubi H , Bahrami F , ,Lucas ,C. Path planning inan environment with static and dynamic obstacles using genetic algorithm : a simplified search space approach [C]. Memphis : IEEE Congress on Evolutionary Computation ,2006.
[9]. L1 Q,Liu G,Wei Z,et al. A specific genetic algorithm for optimum path planning in intelligent transportation system[C] . Lincoln : International Conference on Its Telecommunications ,2007.
[10]. Lin C,Yu J,Liu J,et . Genetic algorithm for shortest driving time in intelligent transportation systems [C] . Dallas : International Conference on Multimedia and UbiqutiousEngineering, 2008
[11]. Kumar A , Arunadevi J , Mohan V. Intelligent transport route planning using genetic algorithms in path computation algorithms [J]. European Journal of Scientific Research , 2009,25 (3) ;463 -468.
[12]. Colomi A. Distributed optimization by ant colonies [C] . Boston : Proceedings of the First European Conference on Artificial Life,1991.
[13]. Fan X , Xiong L , Sheng Y, et al. Optimal path planning for mobile robots based on intensified ant colony optimization algorithm [C] . Shanghai : International Conference on Robotics , IEEE , 2003.
[14]. Hsiao Y T,Chuang C L,Chien C C. Ant colony optimization for best path planning [C]. Tokoyo : IEEE International Symposium on Communications & Information Technology ,2004.
[15]. Zhu Qingbao , Zhang Yulan. An ant colony algorithm based on grid method for mobile robot path planning[J] . Robot, 2005, 27(2) ;132-136.
[16]. Attiratanasunthron N , Fakcharoenphol J. A running time analysis of an ant colony optimization algorithm for shortest paths in directed acyclic graphs [J]. Information Processing Letters, 2008,105(3) ;88-92.
[17]. Liu Changan , Yan Xiaohu , Liu Chunyang , et al. Dynamic path planning for mobile robot based on improved ant colony optimization algorithm [J]. Acta Electronica Sinica , 2011,39 (5):1220-1224.
[18]. Shi Enxiu , Chen Minmin , Li Jun , et al. Research on method of global path – planning for mobile robot based on ant colony algorithm [J]. Transactions of the Chinese Society for Agricultural Machinery ,2014,45(6);53 — 57.
[19]. Zuo L, Lei S, Dong S, et al. A Multi – objective optimization scheduling method based on the antcolony algorithm in cloud computing [J]. IEEE Access ,2017,3(1) ;2687 — 2699.
Cite this article
Sun,P. (2023). A review of research on directional off-road path planning algorithms. Applied and Computational Engineering,4,750-754.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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References
[1]. Ge W.Y., Li P.. Secure A* algorithm for path planning of mobile robots [J/OL]. Journal of Huaqiao University
[2]. KHATIB O.Real-time obstacle avoidance for manipulatorsand mobile robots[C]//ProceedingsIEEE InternationalCon-ference on Robotics and Automation，1985;500-505.
[3]. Luo Q., Wang H. B., Cui S. J., et al. Improved artificial potential field method for autonomous mobile robot path planning [J]. Control Engineering, 2019, 26(6): 1091-1098.
[4]. Guo Lopeng. Research on path planning algorithm based on improved artificial potential field method [D]. Harbin: Harbin Institute of Technology, 2017.
[5]. Juidette H , Youlal H. Fuzzy dynamic path planning using genetic algorithms [J]. Electronics Letters ,2000,36(4);374—376.
[6]. Zhang Feizhou, Yan Lei , Fan Yuezu , et al. Optimizing dis patching of public traffic vehicles in intelligent transport system[J] . Journal of Beijing University of Aeronautics and Astronautics ,2002,28(6) ;707-710.
[7]. Yu L, Gong J, Zhang J, et al. Genetic — algorithm — based path optimization methodology for spatial decision [C]. Los Angeles : Geoinformatics , Geospatial Information Science. International Society for Optics and Photonics ,2006.
[8]. Mahjoubi H , Bahrami F , ,Lucas ,C. Path planning inan environment with static and dynamic obstacles using genetic algorithm : a simplified search space approach [C]. Memphis : IEEE Congress on Evolutionary Computation ,2006.
[9]. L1 Q,Liu G,Wei Z,et al. A specific genetic algorithm for optimum path planning in intelligent transportation system[C] . Lincoln : International Conference on Its Telecommunications ,2007.
[10]. Lin C,Yu J,Liu J,et . Genetic algorithm for shortest driving time in intelligent transportation systems [C] . Dallas : International Conference on Multimedia and UbiqutiousEngineering, 2008
[11]. Kumar A , Arunadevi J , Mohan V. Intelligent transport route planning using genetic algorithms in path computation algorithms [J]. European Journal of Scientific Research , 2009,25 (3) ;463 -468.
[12]. Colomi A. Distributed optimization by ant colonies [C] . Boston : Proceedings of the First European Conference on Artificial Life,1991.
[13]. Fan X , Xiong L , Sheng Y, et al. Optimal path planning for mobile robots based on intensified ant colony optimization algorithm [C] . Shanghai : International Conference on Robotics , IEEE , 2003.
[14]. Hsiao Y T,Chuang C L,Chien C C. Ant colony optimization for best path planning [C]. Tokoyo : IEEE International Symposium on Communications & Information Technology ,2004.
[15]. Zhu Qingbao , Zhang Yulan. An ant colony algorithm based on grid method for mobile robot path planning[J] . Robot, 2005, 27(2) ;132-136.
[16]. Attiratanasunthron N , Fakcharoenphol J. A running time analysis of an ant colony optimization algorithm for shortest paths in directed acyclic graphs [J]. Information Processing Letters, 2008,105(3) ;88-92.
[17]. Liu Changan , Yan Xiaohu , Liu Chunyang , et al. Dynamic path planning for mobile robot based on improved ant colony optimization algorithm [J]. Acta Electronica Sinica , 2011,39 (5):1220-1224.
[18]. Shi Enxiu , Chen Minmin , Li Jun , et al. Research on method of global path – planning for mobile robot based on ant colony algorithm [J]. Transactions of the Chinese Society for Agricultural Machinery ,2014,45(6);53 — 57.
[19]. Zuo L, Lei S, Dong S, et al. A Multi – objective optimization scheduling method based on the antcolony algorithm in cloud computing [J]. IEEE Access ,2017,3(1) ;2687 — 2699.