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计算机工程 ›› 2011, Vol. 37 ›› Issue (8): 216-218.

• 人工智能及识别技术 • 上一篇    下一篇

基于BQPSO的潜水器路径规划算法

韩应贤,刘 静,朱大奇   

  1. (上海海事大学水下机器人与智能系统实验室,上海 201306)
  • 出版日期:2011-04-20 发布日期:2012-10-31
  • 作者简介:韩应贤(1984-),男,硕士研究生,主研方向:智能优化算法;刘 静,讲师;朱大奇,教授、博士生导师
  • 基金资助:
    上海市晨光计划基金资助项目(2008CG55);上海市教委创新基金资助项目(10YZ113, 10ZZ97)

Path Planning Algorithm for Underwater Vehicle Based on BQPSO

HAN Ying?-xian, LIU Jing, ZHU Da-qi   

  1. (Laboratory of Underwater Vehicles and Intelligent Systems, Shanghai Maritime University, Shanghai 201306, China)
  • Online:2011-04-20 Published:2012-10-31

摘要: 在栅格法的自治水下机器人离散工作空间基础上,提出一种基于二进制编码的量子粒子群(BQPSO)算法求解自治水下机器人路径规划问题。该算法将路径表示为粒子位置的二进制编码,以路径长度为适应值,引入交叉策略避免陷入局部最小。仿真实验表明,BQPSO算法可以进行有效的自治水下机器人路径避障。

关键词: 粒子群优化算法, 量子粒子群优化算法, 二进制量子粒子群优化算法, 路径规划

Abstract: A method of path planning for underwater vehicle based on Binary Quantum-behaved Particle Swarm Optimization(BQPSO) algorithm is proposed aiming at the grid discrete workspace. In this algorithm, the path is represented as binary code of the particle position. The length of path is set as function fitness and the crossover is introduced to avoid the local minima. Simulation experiments show that BQPSO algorithm can effectively avoid the obstacle of the underwater vehicle.

Key words: Particle Swarm Optimization(PSO) algorithm, Quantum-behaved PSO(QPSO) algorithm, Binary QPSO(BQPSO) algorithm, path planning

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