基于FCGA的多机器人士兵协同式搜寻问题研究
详细信息 查看官网全文
- 英文论文题名：Research on Collaborative Search of Multi-Robot Soldiers Based on FCGA
- 论文作者：徐志雄 ; 曹雷 ; 陈希亮
- 英文论文作者：XU Zhi-xiong ; CAO Lei ; CHEN Xi-liang ; Institute of Command Information System ; PLA University of Science and Technology
- 年：2017
- 作者机构：解放军理工大学指挥信息系统学院;
- 论文关键词：机器人 ; 模糊逻辑 ; 混沌因子 ; 遗传算法 ; 协同搜寻
- 英文论文关键词：Robot ; Fuzzy Logic ; Chaotic Factor ; Genetic Algorithm ; Collaborative Search
- 会议召开时间：2017-07-03
- 会议录名称：第五届中国指挥控制大会论文集
- 语种：中文
- 分类号：TP18;TP242
- 学会代码：ZHKZ
- 会议名称：第五届中国指挥控制大会
- 会议地点：中国北京
- 主办单位：中国指挥与控制学会
- 学会名称：中国指挥与控制学会
- 页数：6
- 文件大小：783k
- 原文格式：D
- 会议级别：全国
摘要
本文提出了基于FCGA的多机器人系统协同式搜寻方法,首先,利用随机算法实现基本的搜寻和避障优化,在此基础上运用遗传算法优化机器人的搜索过程,针对遗传算法容易早熟的问题,引入混沌操作对遗传算法进行改进;其次,采用模糊逻辑计算种群适应度函数,从分散度、同向度、区域不同度和比较度四个方面实现多机器人系统之间的交互以及协同搜寻;最后,通过与随机算法、简单遗传算法的仿真结果比较,证明了基于FCGA的搜寻方法的实用性和高效性。
A novel algorithm based on FCGA is proposed. Firstly, the stochastic algorithm is used to realize the basic searching and avoiding obstacles optimization. On this basis, the genetic algorithm is used to optimize the searching process of the robot. In order to solve the problem that the genetic algorithm is easy to be premature, The genetic algorithm is improved, the fuzzy fitness function is used to calculate the population fitness function, and the interaction and co-search are realized from the four aspects of dispersion degree, Finally, compared with the results of stochastic algorithm and simple genetic algorithm, the FCGA-based search method is proved to be practical and efficient.
A novel algorithm based on FCGA is proposed. Firstly, the stochastic algorithm is used to realize the basic searching and avoiding obstacles optimization. On this basis, the genetic algorithm is used to optimize the searching process of the robot. In order to solve the problem that the genetic algorithm is easy to be premature, The genetic algorithm is improved, the fuzzy fitness function is used to calculate the population fitness function, and the interaction and co-search are realized from the four aspects of dispersion degree, Finally, compared with the results of stochastic algorithm and simple genetic algorithm, the FCGA-based search method is proved to be practical and efficient.
引文
[1]刘晓明,曹雷,鲍广宇,等.无人化指挥控制初探[C].报告文集——院士专家解读网络时代的指挥与控制,北京:国防工业出版社,2013.
[2]Miura J,Kadekawa S,Chikaarashi K,et al.Human-Robot Collaborative Remote Object Search[M]//Intelligent Autonomous Systems 13.Springer International Publishing,2016:979-991.
[3]Macwan A,Vilela J,Nejat G,et al.Multi-robot deployment for wilderness search and rescue[J].2016,31(1).
[4]Cai B,Zhang Y.Different-Level Redundancy-Resolution and Its Equivalent Relationship Analysis for Robot Manipulators Using Gradient-Descent and Zhang's Neural-Dynamic Methods[J].IEEE Transactions on Industrial Electronics,2012,59(8):3146-3155.
[5]Li J,Li M,Li Y,et al.Coordinated multi-robot target hunting based on extended cooperative game[C].IEEE International Conference on Information and Automation.IEEE,2015:216-221.
[6]Konur S,Dixon C,Fisher M.Analysing robot swarm behavior via probabilistic model checking[J].Robotics and Autonomous Systems,2012,60(2):199-213.
[7]Mario E L D.Distributed Multi-Robot Learning using Particle Swarm Optimization[J].International Journal of Intelligent Systems,2015,21(2):209—226.
[8]Xu X,Hu N,Xu Y,et al.Application of improved firefly algorithm in path planning[J].Journal of Electronic Measurement&Instrumentation,2016.
[9]张云正,薛颂东,曾建潮.群机器人多目标搜索中的合作协同和竞争协同[J].机器人,2015(2):142-151.
[10]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.
[11]Wang X,Shi Y,Ding D,et al.Double global optimum genetic algorithm–particle swarm optimization-based welding robot path planning[J].Engineering Optimization,2015,48(2):1-18.
[12]Calaiselvy C,Yong F T,Ping L W.A Genetic Algorithm for Robot Navigation[J].Mathematical Problems in Engineering,2016,2016:1-10.
[13]Tang Q R,Eberhard P.A PSO-based algorithm designed for a swarm of mobile robots[J].Structural and Multidisciplinary Optimization,2011,44(4):483-498.
[14]冯艳红,刘建芹,贺毅朝.基于混沌理论的动态种群萤火虫算法[J].计算机应用,2013,33(3):796-799.
[15]Khazaii J.Genetic Algorithm Optimization[M].Advanced Decision Making for HVAC Engineers.Springer International Publishing,2016.
[16]Banerjee C,Datta D,Agarwal A.Chaotic Patrol Robot with Frequency Constraints[C].IEEE international conference on research in computational intelligence and communication networks.2015.
[17]Li C,Song Y,Wang F,et al.Chaotic Path Planner of Autonomous Mobile Robots Based on the Standard Map for Surveillance Missions[J].Mathematical Problems in Engineering,2015,2015:1-11.
[18]Inukai H,Minami M,Yanou A.Generating chaos with neuralnetwork-differential-equation for intelligent fish-catching robot[C].Control Conference.IEEE,2015:1-6.
[19]Samant R,Nair S,Kazi F.Development of Autonomous Humanoid Robot Control for Competitive Environment Using Fuzzy Logic and Heuristic Search[J].Ifac Papersonline,2016,49(1):373-378.
[20]Neyoy H,Castillo O,Soria J.Fuzzy Logic for Dynamic Parameter Tuning in ACO and Its Application in Optimal Fuzzy Logic Controller Design[M].Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics.Springer International Publishing,2015:3-28.
[2]Miura J,Kadekawa S,Chikaarashi K,et al.Human-Robot Collaborative Remote Object Search[M]//Intelligent Autonomous Systems 13.Springer International Publishing,2016:979-991.
[3]Macwan A,Vilela J,Nejat G,et al.Multi-robot deployment for wilderness search and rescue[J].2016,31(1).
[4]Cai B,Zhang Y.Different-Level Redundancy-Resolution and Its Equivalent Relationship Analysis for Robot Manipulators Using Gradient-Descent and Zhang's Neural-Dynamic Methods[J].IEEE Transactions on Industrial Electronics,2012,59(8):3146-3155.
[5]Li J,Li M,Li Y,et al.Coordinated multi-robot target hunting based on extended cooperative game[C].IEEE International Conference on Information and Automation.IEEE,2015:216-221.
[6]Konur S,Dixon C,Fisher M.Analysing robot swarm behavior via probabilistic model checking[J].Robotics and Autonomous Systems,2012,60(2):199-213.
[7]Mario E L D.Distributed Multi-Robot Learning using Particle Swarm Optimization[J].International Journal of Intelligent Systems,2015,21(2):209—226.
[8]Xu X,Hu N,Xu Y,et al.Application of improved firefly algorithm in path planning[J].Journal of Electronic Measurement&Instrumentation,2016.
[9]张云正,薛颂东,曾建潮.群机器人多目标搜索中的合作协同和竞争协同[J].机器人,2015(2):142-151.
[10]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.
[11]Wang X,Shi Y,Ding D,et al.Double global optimum genetic algorithm–particle swarm optimization-based welding robot path planning[J].Engineering Optimization,2015,48(2):1-18.
[12]Calaiselvy C,Yong F T,Ping L W.A Genetic Algorithm for Robot Navigation[J].Mathematical Problems in Engineering,2016,2016:1-10.
[13]Tang Q R,Eberhard P.A PSO-based algorithm designed for a swarm of mobile robots[J].Structural and Multidisciplinary Optimization,2011,44(4):483-498.
[14]冯艳红,刘建芹,贺毅朝.基于混沌理论的动态种群萤火虫算法[J].计算机应用,2013,33(3):796-799.
[15]Khazaii J.Genetic Algorithm Optimization[M].Advanced Decision Making for HVAC Engineers.Springer International Publishing,2016.
[16]Banerjee C,Datta D,Agarwal A.Chaotic Patrol Robot with Frequency Constraints[C].IEEE international conference on research in computational intelligence and communication networks.2015.
[17]Li C,Song Y,Wang F,et al.Chaotic Path Planner of Autonomous Mobile Robots Based on the Standard Map for Surveillance Missions[J].Mathematical Problems in Engineering,2015,2015:1-11.
[18]Inukai H,Minami M,Yanou A.Generating chaos with neuralnetwork-differential-equation for intelligent fish-catching robot[C].Control Conference.IEEE,2015:1-6.
[19]Samant R,Nair S,Kazi F.Development of Autonomous Humanoid Robot Control for Competitive Environment Using Fuzzy Logic and Heuristic Search[J].Ifac Papersonline,2016,49(1):373-378.
[20]Neyoy H,Castillo O,Soria J.Fuzzy Logic for Dynamic Parameter Tuning in ACO and Its Application in Optimal Fuzzy Logic Controller Design[M].Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics.Springer International Publishing,2015:3-28.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |