Computer Science ›› 2017, Vol. 44 ›› Issue (9): 290-295.doi: 10.11896/j.issn.1002-137X.2017.09.054

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Obstacle Avoidance Path Planning for Irregular Obstacles

JIA Chun-xue, LUO Qi and GONG Yang-yang   

  • Online:2018-11-13 Published:2018-11-13

Abstract: The phenomenon of path redundancy and high energy consumption exist in the traditional multi-agent obstacle avoidance algorithms when the shape of the obstacle is considered,and the algorithms are not universal.Therefore,firstly,the method of automatic recognition convexity was defined to transform the obstacle from irregular to rule.Secondly,inspired by the idea of sub-target,the path of the agent was transformed into the superposition of multiple landing points of the obstacle after being ruled,so as to ensure the optimization of each path,and then selected the global optimal path.Finally,MATLAB was used to simulate,compare and analyze the results of the other two algorithms,and the feasibility and effectiveness of the algorithm was verified.

Key words: Irregular,Path planning,Automatic recognition convexity,Landing point

[1] BARANOV M I.An anthology of outstanding achievements in science and technology.Part 21:Artificial intelligence and robo-tics[J].Electrical Engineering & Electromechanics,2014(4):3-14.
[2] KIM Y,BANB H.Decentralized control of multiple unmannedaircraft for target tracking and obstacle avoidance[C]∥International Conference on Unmanned Aircraft Systems.IEEE,2016:327-331.
[3] GAO Y,WEI Z Q,GONG F X,et al.Dynamic Path Planning for Underwater Vehicles Based on Modified Artificial Potential Field Method[C]∥2013 Fourth International Conference on Digital Manufacturing & Automation.2013:518-521.
[4] XU T F,LUO Q,WANG H.Dynamic path planning for mobile robot based on vector field[J].Computer Science,2015,42(5):237-243.(in Chinese) 徐腾飞,罗琦,王海.基于向量场的移动机器人动态路径规划[J].计算机科学,2015,42(5):237-243.
[5] WANG M.Research on Robot Obstacle Avoidance Planning Basedon Evolutionary Computation and Visualization[D].Shenyang:Shenyang University of Technology,2014.(in Chinese) 王猛.基于进化计算及可视图的机器人避障规划研究[D].沈阳:沈阳工业大学,2014.
[6] OUYANG X Y,YANG S G.Obstacle Avoidance Path Planning of Mobile Robots Based on Potential Grid Method[J].Control Engineering of China,2014(1):134-137.
[7] ZHANG B F,WANG Y C,ZHANG X L.Mobile Robot PathPlanning Based on Artificial Potential Field Method[J].Applied Mechanics & Materials,2014,577:350-353.
[8] SHAN B M,ZHOU P P.Simulation study on mobile robot path planning based on improved potential field[J].Information Technology,2014(1):178-181.
[9] WU Z S,FU W P.A Review of Path Planning Method for Mobile Robot[J].Advanced Materials Research,2014,1030:1588-1591.
[10] KIM B K,TANAKA H,SUMI Y.Topological Graph BasedBoundary Coverage Path Planning for a Mobile Robot[C]∥ 2013 Int.Symp.Artificial Life and Robotics(AROB 2013).Daejeon,Korea,2013:496-497.
[11] LIU Y.Generation and optimization of obstacle avoidance path based on visual graph method[D].Kunming:Kunming University of Science and Technology,2012.(in Chinese) 刘娅.基于可视图法的避障路径生成及优化[D].昆明:昆明理工大学,2012.
[12] YANG J,HE L L,LI R L,et al.Path Planning for Robot Based on Improved Potential Grid[J].Coal Mine Machinery,2012,33(8):74-76.
[13] WANG Y,CHEN W.Path planning and obstacle avoidance of unmanned aerial vehicle based on improved genetic algorithms[C]∥Chinese Control Conference.2014:8612-8616.
[14] LI J,LI W.Study on the path planning of mobile robot based on fuzzy control[J].Journal of Chinese Agricultural Mechanization,2015(1):272-274.
[15] GAUTAM S A,VERMA N.Path planning for unmanned aerial vehicle based on genetic algorithm & artificial neural network in 3D[C]∥International Conference on Data Mining and Intelligent Computing.IEEE,2014:1-5.
[16] WEN R,LI D W,LUAN X F,et al.Robot path planning based on ant colony algorithm[J].Computer and Digital Engineering,2012,40(5):20-22.(in Chinese) 温瑞,李大伟,栾孝丰,等.基于蚁群算法的机器人路径规划[J].计算机与数字工程,2012,40(5):20-22.
[17] QIU L L.Robot path planning based on improved ant colony algorithm [D].Shanghai:Donghua University,2015.(in Chinese) 邱莉莉.基于改进蚁群算法的机器人路径规划[D].上海:东华大学,2015.
[18] LIU K,YOU X M,LIU S.Improved ant colony algorithm for path planning of mobile robot in complex environment[J].Computer Engineering and Application,2016,52(13):60-63.(in Chinese) 刘锴,游晓明,刘升.复杂环境移动机器人路径规划的改进蚁群算法[J].计算机工程与应用,2016,52(13):60-63.
[19] PENG L.Path planning of mobile robot based on genetic algorithm[D].Changsha:Changsha University of Science and Technology,2013.(in Chinese) 彭丽.基于遗传算法的移动机器人路径规划[D].长沙:长沙理工大学,2013.
[20] LI T X,CHEN G D.Path planning of indoor mobile robot based on improved genetic algorithm [J].Manufacturing Automation,2015(20):31-35.(in Chinese) 李天旭,陈广大.基于改进遗传算法的室内移动机器人路径规划[J].制造业自动化,2015(20):31-35.
[21] ZHANG Y,DAI E C,LUO Y.Path planning of mobile robot based on improved genetic algorithm[J].Computer Measurement and Control,2016,24(1):313-316.(in Chinese) 张毅,代恩灿,罗元.基于改进遗传算法的移动机器人路径规划[J].计算机测量与控制,2016,24(1):313-316.
[22] ZHU Y Y.Path planning of mobile robot based on hybrid particle swarm optimization[D].Shanghai:Shanghai University of Engineering Science,2015.(in Chinese) 朱莹莹.基于混合粒子群算法的移动机器人路径规划研究[D].上海:上海工程技术大学,2015.
[23] WANG Y,CAO W.A global path planning method for mobile robot based on a three-dimensional-like map[J].Robotica,2013,32(4):611-624.
[24] HOU Z W,JIA Y L,WANG Z H,et al.Research on jewelry po-sitioning technology based on the minimum bounding rectangle[J].Computer Engineering,2016,42(2):254-260.(in Chinese) 侯占伟,贾玉兰,王志衡,等.基于最小外接矩形的珠宝定位技术研究[J].计算机工程,2016,42(2):254-260.

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