[1]莫宏伟,马靖雯.一种生物地理学移动机器人路径规划算法[J].智能系统学报编辑部,2015,10(5):705-711.[doi:10.11992/tis.201407003]
MO Hongwei,MA Jingwen.A biogeography-based mobile robot path planning algorithm[J].CAAI Transactions on Intelligent Systems,2015,10(5):705-711.[doi:10.11992/tis.201407003]
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MO Hongwei,MA Jingwen.A biogeography-based mobile robot path planning algorithm[J].CAAI Transactions on Intelligent Systems,2015,10(5):705-711.[doi:10.11992/tis.201407003]
一种生物地理学移动机器人路径规划算法
《智能系统学报》编辑部[ISSN 1673-4785/CN 23-1538/TP] 卷:
10
期数:
2015年第5期
页码:
705-711
栏目:
学术论文—智能系统
出版日期:
2015-10-25
- Title:
- A biogeography-based mobile robot path planning algorithm
- Keywords:
- mobile robot; path planning; biogeography-based optimization (BBO); effective vertex; grid coding method
- 分类号:
- TP301
- 文献标志码:
- A
- 摘要:
- 目前,虽然有多种智能计算方法用于移动机器人路径规划问题,但在复杂环境下,多数智能计算方法表现出效率低下,结果较差的问题。提出一种结合基于有效顶点的栅格编码法和改进的生物地理学优化算法的移动机器人路径规划方法,以解决该类问题。结合已知的环境信息,从精英策略、降维机制和基于惯性算子的迁移操作3方面改进了生物地理学优化算法。改进算法用于机器人移动路径,与人工蜂群算法、粒子群算法和人工鱼群算法等智能算法进行比较,实验的结果证实改进算法能够更有效地解决复杂环境下机器人路径规划问题。
- Abstract:
- At present, there are many intelligent computing methods used in mobile robot path planning; however, in complex environments, most of them have low efficiency and poor results. In order to solve such problems, this paper proposes a new method for mobile robot path planning, which combines the grid coding method based on the effective vertex with the improved biogeography-based optimization (BBO). On the basis of the environmental infor-mation that has been learned, the BBO is improved in three aspects:elite strategies, dimension reduction mecha-nisms and migration based on inertial operator. The improved BBO is applied in path planning. The method is com-pared with artificial bee colony (ABC), particle swarm optimization (PSO) and artificial fish algorithm (AFA). Experiment results show that the improved method can solve the problem of mobile robot path planning in a complex environment more efficiently.
- 参考文献/References:
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备注/Memo
收稿日期:2014-07-01;改回日期:。
基金项目:中央高校基本科研业务经费资助项目(HEUCFX041306).
作者简介:莫宏伟,男,1973年生,教授,主要研究方向为自然计算理论与应用、机器人、机器学习与数据挖掘。主持完成国家自然科学基金等国家、省部级及横向课题16项,获得省科技进步奖2项,发表学术论文60余篇,其中被SCI检索11篇,EI检索40篇;马靖雯,女,1988年生,硕士研究生,主要研究方向为自然计算及其应用。
通讯作者:莫宏伟.E-mail:honwei2004@126.com.
更新日期/Last Update:
2015-11-16