计算机科学 ›› 2020, Vol. 47 ›› Issue (11): 220-225.doi: 10.11896/jsjkx.190900026
陈骏岭, 秦小麟, 李星罗, 周杨淏, 鲍斌国
CHEN Jun-ling, QIN Xiao-lin, LI Xing-luo, ZHOU Yang-hao, BAO Bin-guo
摘要: 近年来,随着社会对机器人关注度的增加,移动机器人技术逐渐成为研究热点。机器人避障是移动机器人学中重要的研究课题,也是移动机器人面临的基本问题之一。针对多机器人的应用场景,在充分分析现有机器人避障算法的基础上,优化人工势场法,提出多机器人避障算法MPF(Multi-Robot Artificial Potential Field Method)和编队避障算法AOA(Advanced Obstacle Avoidance Method)。MPF算法优化了人工势场法存在局部最小值点的问题,提高了机器人到达目标点的概率;AOA算法结合现有的编队避障算法来提高机器人编队避障的效率。最后,分别为MPF算法和AOA算法设计不同的实验环境,实验结果表明,在障碍物复杂情况不同的环境中MPF算法可以有效且高效地引导机器人到达目标点;在不同的环境复杂度和机器人数量下,AOA算法能够提供高效稳定的编队避障。
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[1] SUJIT P B,SARIPALLI S,SOUSA J B.Unmanned Aerial Vehicle Path Following:A Survey and Analysis of Algorithms for Fixed-Wing Unmanned Aerial Vehicless[J].IEEE Control Systems,2014,34(1):42-59. [2] LIU Z,YUAN C,YUX,et al.Fault-Tolerant Formation Control of Unmanned Aerial Vehicles in the Presence of Actuator Faults and Obstacles[J].Unmanned Systems,2016,4(3):197-211. [3] BROOKS R S.A robust layered control system for a mobile robot[J].IEEE J.robot.Autom,1986,2(1):14-23. [4] MAES P.A Bottom-up Mechanism for Behavior Selection in an Artificial Creature[C]//Proceedings of the First International Conference on Simulation of Adaptive Behavior.MIT Press,1991. [5] ARKIN R.Motor schema based navigation for a mobile robot:An approach to programming by behavior[C]//IEEE International Conference on Robotics & Automation.1987. [6] CHEN Y S,JUANG J G.Intelligent obstacle avoidance control strategy for wheeled mobile robot[C]//ICCAS-SICE.2009:3199-3204. [7] MENG J E,CHANG D.Obstacle avoidance of a mobile robot using hybrid learning approach[J].IEEE Transactions on Industrial Electronics,2005,52(3):898-905. [8] RAM A,BOONE G,ARKIN R C,et al.Using Genetic Algo-rithms to Learn Reactive Control Parameters for Autonomous Robotic Navigation[J].Adaptive Behavior,1994,2(3):277-305. [9] PIAO S H,HONG B R.Robot path planning using genetic algorithms[J].Journal of Harbin Institute of Technology,2001,8(3):215-217. [10] TU J,YANG S X.Genetic algorithm based path planning for a mobile robot[C]//IEEE International Conference on Robotics &Automation.2003. [11] QIAO L,LU Y,XIE C.Optimal Genetic Fuzzy Obstacle Avoidance Controller of Autonomous Mobile Robot Based on Ultrasonic Sensors[C]//IEEE International Conference on Robotics &Biomimetics.2007. [12] XU X,XIE J,XIE K.Path Planning and Obstacle-Avoidance for Soccer Robot Based on Artificial Potential Field and Genetic Algorithm[C]//World Congress on Intelligent Control & Automation.2006. [13] KHATIB O.Real-Time Obstacle Avoidance for Manipulatorsand Mobile Robots[J].International Journal of Robotics Research,1986,5(1):90-98. [14] YUN X,TAN KC.A wall-following method for escaping local minima in potential field based motion planning[C]//International Conference on Advanced Robotics.1997. [15] Keisuke SATO.Deadlock-free motion planning using the Laplace potential field[J].Advanced Robotics,1992,7(5):13. [16] ZHANG Y,LI X.Leader-follower formation control and obstacle avoidance of multi-robot based on artificial potential field[C]//Control & Decision Conference.2015. [17] CHEN J,SUN D,YANG J,et al.Leader-Follower FormationControl of Multiple Non-holonomic Mobile Robots Incorporating a Receding-horizon Scheme[J].International Journal of Robotics Research,2010,29(6):727-747. [18] MOHAMED E F,ELMETWALLY K,HANAFY A R.An improved Tangent Bug method integrated with artificial potential field for multi-robot path planning[C]//International Sympo-sium on Innovations in Intelligent Systems & Applications.2011. [19] QUS Z.Research on swarm robot formation and cooperative obstacle avoidance method[D].Nanjing:Nanjing University,2015. [20] QING L,ZHOU Z,SHANGJUN W,et al.Path planning in environment with moving obstacles for mobile robot[C]//Proceedings of the 31st Chinese Control Conference.IEEE,2012:5019-5024. [21] GE S S,CUIY J.Dynamic Motion Planning for Mobile Robots Using Potential Field Method[J].Autonomous Robots,2002,13(3):207-222. |
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