[1]唐小勇,于 飞,潘洪悦.改进粒子群算法的潜器导航规划[J].智能系统学报,2010,5(5):443-448.[doi:10.3969/j.issn.1673-4785.2010.05.011]
TANG Xiao-yong,YU Fei,PAN Hong-yue.Submersible path-planning based on an improved PSO[J].CAAI Transactions on Intelligent Systems,2010,5(5):443-448.[doi:10.3969/j.issn.1673-4785.2010.05.011]
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TANG Xiao-yong,YU Fei,PAN Hong-yue.Submersible path-planning based on an improved PSO[J].CAAI Transactions on Intelligent Systems,2010,5(5):443-448.[doi:10.3969/j.issn.1673-4785.2010.05.011]
改进粒子群算法的潜器导航规划
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
5
期数:
2010年第5期
页码:
443-448
栏目:
学术论文—智能系统
出版日期:
2010-10-25
- Title:
- Submersible path-planning based on an improved PSO
- 文章编号:
- 1673-4785(2010)05-0443-06
- 分类号:
- TP242.6
- 文献标志码:
- A
- 摘要:
- 针对粒子群算法的寻优搜索能力强和已有的一些导航算法存在收敛速度慢、迭代时间长的缺点，提出一种基于粒子群算法的潜器导航算法.利用群智能理论，对基本粒子群算法进行改进：提出一个含突变因子的可变调的惯性权值策略，从而达到增强粒子群算法局部和全局寻优的调度能力.通过实验仿真验证，证明了改进粒子群算法具有更优的性能.在此基础上，将该算法应用到水下潜器的路径规划中，通过对环境的建模分析进行条件约束，最终将路径规划问题转化为路径点求解的优化问题.实验仿真结果获得了从起点到终点的无碰撞路径，收敛速度也较快，验证了该方法的有效性和可行性.
- Abstract:
- To overcome the shortcomings in slow convergence speed and long iteration time in the existing algorithms, take advantage of the searching ability of a particle swarm optimization (PSO), a new navigation algorithm was created based on PSO. First, the theory of swarm intelligence was used to improve the basic PSO algorithm: proposing a transformable inertia weight which contains a mutation factor to improve the PSO, and thereby enhancing the local and global optimum capability of PSO. Through experimental simulation and validation, the better performance of the improved PSO (IPSO) was proven. On this basis, the IPSO was used in path planning of an underwater vehicle. By using modeling analysis of space and adding constraint conditions, the path planning problem was converted into an optimization problem concerning solutions of path points. Finally, through experimental simulation, a collisionfree path from start to finish was given, proving the validity and feasibility of this method.
- 参考文献/References:
-
［1］肖本贤,李善寿,王晓伟,等.基于PSO和人工势场的机器人路径规划［J］.合肥工业大学学报, 2007, 30(6): 718-722.
XIAO Benxian, LI Shanshou, WANG Xiaowei, et al. Path planning of mobile robots based on PSO and APF［J］. Journal of Hefei University of Techenology, 2007, 30 (6): 718-722.
［2］张帆,周庆敏.基于遗传算法的移动机器人路径规划仿真［J］.微计算机信息, 2008, 24(6): 267-268， 284.
ZHANG Fan, ZHOU Qingmin. A method based genetic for path of a mobile robot［J］. Microcomputer Information，2008, 24(6): 267-268， 284.
［3］SARIMVEISH H, ALEXANDRIDIS A, MAZARAKISS, et al. A new algorithm for developing dynamic radial basis function neural network models based on genetic algorithms［J］. Computers and Chemical Engineering, 2004, 28(1/2): 209-217.
［4］宋勇,李贻斌,栗春,等.基于神经网络的移动机器人路径规划方法［J］.系统工程与电子技术, 2008, 30(2): 316-319.
SONG Yong, LI Yibin, LI Chun, et al. Path planning methods of mobile robot based on neural network［J］. Systems Engineering and Electronics, 2008, 30(2): 316-319.
［5］张建英,刘暾.基于人工势场法的移动机器人最优路径规划［J］.航空学报, 2007, 8(2): 45-48.
ZHANG Jianying, LIU Tun. Optimized path planning of mobile robot based on artificial potential field［J］. Acta Aeronautica et Astronautica Sinica, 2007, 8(2): 45-48.
［6］孙波,陈卫东,席裕庚.基于粒子群优化算法的移动机器人全局路径规划［J］.控制与决策, 2005(9): 1052-1055.
SUN Bo, CHEN Weidong, XI Yugeng. Particle swarm optimization based global path planning for mobile robots［J］. Control and Decision, 2005(9): 1052-1055.
［7］KENNEDY J, EBERHART R. Particle swarm optimization［C］//IEEE International Conference on Neural Networks. San Diego, USA, 1995: 1942-1948.
［8］KENNEDY J, MENDES R. Neighborhood topologies in-fully-imformed and best of neighborhood particles swarm［J］. IEEE Transactions on Systems, Man, and CyberneticsPart C: Applications and Reviews, 2006, 36(4): 515-519.
［9］郭冰洁,徐玉如,李岳明.水下机器人S面控制器的改进粒子群优化［J］.哈尔滨工程大学学报, 2008, 29(12): 1277-1281.
GUO Bingjie, XU Yuru, LI Yueming. S surface controller for underwater vehicles using particle swarm optimization［J］. Journal of Harbin Engineering University, 2008, 29(12): 1277-1281.
［10］毛宇峰,庞永杰,李晔，等. 速度矢量坐标系下水下机器人动态避障方法［J］. 哈尔滨工程大学学报, 2010, 31(2): 159-164.
MAO Yufeng, PANG Yongjie, LI Ye, et al. Using a velocity vector coordinate method for dynamic obstacle avoidance of autonomous underwater vehicles ［J］. Journal of Harbin Engineering University, 2010, 31(2): 159-164.
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备注/Memo
收稿日期：2009-03-05.
基金项目：国家自然科学基金资助项目(60704001).
通信作者：唐小勇.E-mail：txy_201@163.com.
作者简介：
唐小勇，男，1985年生，硕士研究生，主要研究方向为群智能算法.
于 飞，男，1974年生，教授、博士生导师，主要研究方向为系统仿真与建模.目前承担国家自然科学基金项目2项，博士后基金项目1项，发表学术论文10余篇.
潘洪悦，男，1985年，硕士研究生，主要研究方向为粒子群优化算法.
更新日期/Last Update:
2010-11-26