基于混合混沌序列与遗传算法的排爆机器人路径规划
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摘要
描绘了排爆机器人路径规划问题,提出了混合混沌序列与遗传算法的排爆机器人路径规划算法。针对遗传算法易于陷入局部收敛,在寻优过程中易于出现抖振,算法收敛精度不高等问题,在遗传算法中引入Logistic混沌序列,生成与机器人路径选择更加匹配的优化算法。运用MATLAB进行算法仿真,分析比较经典遗传算法和优化后的算法。仿真结果显示,算法优化后机器人行走路径更加合理,算法的收敛精度提高。
This paper describes the path planning problem of explosive disposal(EOD) robot, and proposes the path planning algorithm with hybrid chaotic sequence and genetic algorithm. Aiming at the problem that genetic algorithm is easy to fall into local convergence, it is prone to chattering in the optimization process, and the convergence accuracy of the algorithm is not high.Logistic chaotic sequences are introduced into the genetic algorithm to generate an optimized algorithm which is more suitable for robot path selection. MATLAB is used to simulate the algorithm, analyze and compare the classical genetic algorithm and the optimized algorithm, the simulation results show that the walking path of the robot with optimized algorithm is more reasonable and the convergence accuracy of the algorithm is improved.
This paper describes the path planning problem of explosive disposal(EOD) robot, and proposes the path planning algorithm with hybrid chaotic sequence and genetic algorithm. Aiming at the problem that genetic algorithm is easy to fall into local convergence, it is prone to chattering in the optimization process, and the convergence accuracy of the algorithm is not high.Logistic chaotic sequences are introduced into the genetic algorithm to generate an optimized algorithm which is more suitable for robot path selection. MATLAB is used to simulate the algorithm, analyze and compare the classical genetic algorithm and the optimized algorithm, the simulation results show that the walking path of the robot with optimized algorithm is more reasonable and the convergence accuracy of the algorithm is improved.
引文
[1]王仲民.移动机器人路径规划与轨迹跟踪[M].兵器工业出版社,2008.
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[4]陈曦,谭冠政,江斌.基于免疫遗传算法的移动机器人实时最优路径规划[J].中南大学学报(自然科学版),2008.3:577-583
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[6]Cai Z,Peng Z.Cooperative Coevolutionary Adaptive Genetic Algorithm in Path Planning of Cooperative Multi-Mobile Robot Systems[J].Journal of Intelligent and Robotic Systems:Theory and Applications,2002.33(1):61-71
[7]司守奎,孙玺菁.数学建模算法与应用[M].国防工业出版社,2017.
[8]江六林.基于混沌映射和DNA编码的图像加密技术的研究与实现[D].南京邮电大学,2016.
[9]刘金波.基于DSP的混沌图像加密系统的实现[D].大连理工大学,2008.
[10]汤任君.Logistic混沌序列和DES算法的图像加密方法[J].计算机应用,2017.37(1):89-92
[11]刘睿.基于改进Logistic混沌映射的图像自适应加密算法[J].计算机与现代化,2016.7:13-17,23
[12]王洲,张毅,杨锐敏.基于遗传算法的移动机器人路径规划[J].微计算机信息,2008.24(26):187-189
[13]王枫红,邓志燕,陈炽坤.基于传统遗传算法的改进排爆机器人路径规划研究[J].图学学报,2012.33(3):41-45
[2]孙树栋,林茂.基于遗传算法的多移动机器人协调路径规划[J].自动化学报,2000.5:672-676
[3]李庆中,顾伟康,叶秀清.基于遗传算法的移动机器人动态避障路径规划方法[J].模式识别与人工智能,2002.15(2):161-166
[4]陈曦,谭冠政,江斌.基于免疫遗传算法的移动机器人实时最优路径规划[J].中南大学学报(自然科学版),2008.3:577-583
[5]Castillo O,Trujillo L,Melin P.Multiple Objective Genetic Algorithms for Path-planning Optimization in Autonomous Mobile Robots[J].Soft Computing,2007.11(3):269-279
[6]Cai Z,Peng Z.Cooperative Coevolutionary Adaptive Genetic Algorithm in Path Planning of Cooperative Multi-Mobile Robot Systems[J].Journal of Intelligent and Robotic Systems:Theory and Applications,2002.33(1):61-71
[7]司守奎,孙玺菁.数学建模算法与应用[M].国防工业出版社,2017.
[8]江六林.基于混沌映射和DNA编码的图像加密技术的研究与实现[D].南京邮电大学,2016.
[9]刘金波.基于DSP的混沌图像加密系统的实现[D].大连理工大学,2008.
[10]汤任君.Logistic混沌序列和DES算法的图像加密方法[J].计算机应用,2017.37(1):89-92
[11]刘睿.基于改进Logistic混沌映射的图像自适应加密算法[J].计算机与现代化,2016.7:13-17,23
[12]王洲,张毅,杨锐敏.基于遗传算法的移动机器人路径规划[J].微计算机信息,2008.24(26):187-189
[13]王枫红,邓志燕,陈炽坤.基于传统遗传算法的改进排爆机器人路径规划研究[J].图学学报,2012.33(3):41-45