[1]吕太之,周武,赵春霞.采用粒子群优化和B样条曲线的改进可视图路径规划算法[J].华侨大学学报(自然科学版),2018,39(1):103-108.[doi:10.11830/ISSN.1000-5013.201702101]
　Lü Taizhi,ZHOU Wu,ZHAO Chunxia.Improved Visibility Graph Method Using Particle Swarm Optimization and B-Spline Curve for Path Planning[J].Journal of Huaqiao University(Natural Science),2018,39(1):103-108.[doi:10.11830/ISSN.1000-5013.201702101]
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采用粒子群优化和B样条曲线的改进可视图路径规划算法()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第39卷
期数:
2018年第1期
页码:
103-108
栏目:
出版日期:
2018-01-17

文章信息/Info

Title:
Improved Visibility Graph Method Using Particle Swarm Optimization and B-Spline Curve for Path Planning
文章编号:
1000-5013(2018)01-0103-06
作者:
吕太之1; 2;  周武3;  赵春霞2
1. 江苏海事职业技术学院 信息工程学院, 江苏 南京 210012;2. 南京理工大学 计算机科学与工程学院, 江苏 南京 210094;3. 浙江师范大学 工学院, 浙江 金华, 321019
Author(s):
Lü Taizhi1; 2;  ZHOU Wu3;  ZHAO Chunxia2
1. School of Information Engineering, Jiangsu Maritime Institute, Nanjing 210012, China; 2. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China; 3. School of Engineering, Zhejiang Normal University, Jinhua 321019, China
关键词:
移动机器人;  局部路径规划;  可视图;  粒子群算法;  B样条曲线
Keywords:
mobile robot;  local path planning;  visibility graph;  particle swarm algorithm;  B-spline curve
分类号:
TP312
DOI:
10.11830/ISSN.1000-5013.201702101
文献标志码:
A
摘要:
针对传统局部路径规划中容易陷入局部陷阱和规划路径不平滑的问题,提出一种将改进可视图,基于B样条曲线和粒子群优化算法结合起来规划一条平滑路径的算法.该算法由多边形动态生成、路径规划和路径平滑3个步骤组成,为了逃离局部陷阱,在多边形动态生成的过程中增加环境记忆功能,并通过路径平滑过程,使规划的路径更能满足移动机器人动力约束条件.仿真实验结果验证了算法的有效性,对比其他几种路径规划算法,所提出算法规划的路径质量更高.
Abstract:
Trapping in local minima and discontinuities often exist in local path planning. To overcome these drawbacks, this paper presents a smooth path planning algorithm based on modified visibility graph which involves B-spline curves and particle swarm optimization. This algorithm consists of three steps: dynamically generate polygons, plan a path and smooth the path. To escape from traps, the environment is memorized in the dynamic polygon generation process. By the path smooth process, this planned path is more adapt the kinetics constraint of mobile robots. Simulations verify the effectiveness of the proposed algorithm. Comparing other several path planning algorithms, the planned path by the proposed algorithm posses a higher quality.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2017-02-02
通信作者: 吕太之(1979-),男,高级工程师,博士,主要从事移动机器人导航技术的研究.E-mail:lvtaizhi@163.com.
基金项目: 国家自然科学基金资助项目(61101197); 江苏省高校优秀中青年教师和校长赴境外研修项目(201121)
更新日期/Last Update: 2018-01-20