Cooperative robot swarm locomotion using genetic algorithms

被引：0
|
作者：
Byington, Matthew D. [1 ]
Bishop, Bradley E. [1 ]
机构：
[1] USN Acad, Annapolis, MD 21412 USA
来源：
PROCEEDINGS OF THE 40TH SOUTHEASTERN SYMPOSIUM ON SYSTEM THEORY | 2008年
关键词：
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
This paper focuses on the design of a decentralized controller for cooperative locomotion in a swarm of robotic agents. Each agent is assumed to be able to locomote over even terrain, grasp other robots, and climb onto a stack of robots. Genetic algorithms and genetic programming methods are applied to develop locomotion controllers for single units as well as decentralized controllers intended to allow the swarm of units to pass over uneven terrain that no single unit can surmount. The goal is to develop a system that provides a high probability of large numbers of units passing through sets of test obstacles. The results are shown through simulation exercises.
引用
收藏
页码：252 / 256
页数：5
相关论文
共 50 条
  • [31] On the Detection Performance of Cooperative Spectrum Sensing Using Particle Swarm Optimization Algorithms
    Shami, Tareq M.
    El-Saleh, Ayman A.
    Kareem, Aymen M.
    2014 IEEE 2ND INTERNATIONAL SYMPOSIUM ON TELECOMMUNICATION TECHNOLOGIES (ISTT), 2014, : 110 - 114
  • [32] Development of Robot Swarm Algorithms on An Extensible Framework
    Bhattacharya, Sambit
    Agrawal, Rajeev
    SOUTHEASTCON 2017, 2017,
  • [33] Survey of Methods and Algorithms of Robot Swarm Aggregation
    Shlyakhov, N. E.
    Vatamaniuk, I. V.
    Ronzhin, A. L.
    INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGIES IN BUSINESS AND INDUSTRY 2016, 2017, 803
  • [34] UAV cooperative multiple task assignments using genetic algorithms
    Shima, T
    Rasmussen, SJ
    Sparks, AG
    ACC: Proceedings of the 2005 American Control Conference, Vols 1-7, 2005, : 2989 - 2994
  • [35] Refinery scheduling optimization using genetic algorithms and cooperative coevolution
    Simao, Leonardo M.
    Dias, Douglas M.
    Pacheco, Marco Aur Lio C.
    2007 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN SCHEDULING, 2007, : 151 - +
  • [36] Cooperative Path Planning of Robot Swarm Based on ACO
    Li Yong
    Li Yu
    Guo Yipei
    Cai Kejie
    PROCEEDINGS OF 2017 IEEE 2ND INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC), 2017, : 1428 - 1432
  • [37] Optimising cancer chemotherapy using particle swarm optimisation and genetic algorithms
    Petrovski, A
    Sudha, L
    McCall, J
    PARALLEL PROBLEM SOLVING FROM NATURE - PPSN VIII, 2004, 3242 : 633 - 641
  • [38] Diagnosis of wiring networks using Particle Swarm Optimization and Genetic Algorithms
    Smail, M. K.
    Bouchekara, H. R. E. H.
    Pichon, L.
    Boudjefdjouf, H.
    Mehasni, R.
    COMPUTERS & ELECTRICAL ENGINEERING, 2014, 40 (07) : 2236 - 2245
  • [39] Optimization of Hexapod Micro Parallel Robot Using Genetic Algorithms
    Stan, Sergiu-Dan
    Maties, Vistrian
    Balan, Radu
    Lapusan, Ciprian
    INNOVATIONS AND ADVANCED TECHNIQUES IN SYSTEMS, COMPUTING SCIENCES AND SOFTWARE ENGINEERING, 2008, : 37 - 42
  • [40] Multiobjective optimisation of robot location in a workcell using genetic algorithms
    Pashkevich, AP
    Pashkevich, MA
    UKACC INTERNATIONAL CONFERENCE ON CONTROL '98, VOLS I&II, 1998, : 757 - 762
12345