未知环境下基于可拓遗传算法的避障算法

doi:10.3778/j.issn.1002-8331.2010.20.062

计算机工程与应用 ›› 2010, Vol. 46 ›› Issue (20): 226-229.DOI: 10.3778/j.issn.1002-8331.2010.20.062

未知环境下基于可拓遗传算法的避障算法

王越超¹，申建芳²

1.广州城市职业学院信息与汽车工程学院，广州 510405
2.广东工业大学计算机学院，广州 510600

收稿日期:2009-12-08 修回日期:2010-05-12 出版日期:2010-07-11 发布日期:2010-07-11
通讯作者: 王越超

Obstacle-avoiding algorithm based on extension genetic algorithm in unknown environment

WANG Yue-chao¹，SHEN Jian-fang²

1.Department of Information and Automobile Engineering，Guangzhou City Polytechnic，Guangzhou 510405，China
2.Faculty of Computer Science，Guangdong University of Technology，Guangzhou 510006，China

Received:2009-12-08 Revised:2010-05-12 Online:2010-07-11 Published:2010-07-11
Contact: WANG Yue-chao

摘要/Abstract

摘要：

为了提高避障机器人的避障能力和对环境的自适应能力，基于可拓遗传算法，对避障机器人的避障方法进行了研究。通过对避障机器人的可拓分析，提出了一种避障机器人物元模型，通过可拓变换重新认知环境信息，设计了相应的可拓适应度函数，改进了遗传操作。通过仿真分析，结果表明，改进后的可拓遗传算法优化了避障机器人的性能，提高了避障机器人对环境的鲁棒性。

关键词: 避障机器人, 可拓变换, 可拓遗传算法

Abstract: To enhance the obstacle-avoiding ability of the obstacle-avoiding robot，and increase the adaptability to the environment，the extension genetic algorithm is adapted.The obstacle-avoiding scheme is studied.Through the extension analysis of the obstacle-avoiding robot，an element model of the obstacle-avoiding robot is put forward.The environmental information is recognized by extension transformation.The reproduction and crossover operation are improved.The corresponding extension fitness function is designed.Through analysis and simulation，results show that the improved extension genetic algorithm improves the performance of the obstacle-avoiding robot and increases the robustness to the environment.

Key words: obstacle-avoiding robot, extension transformation, extension genetic algorithm

中图分类号:

TP242

王越超¹，申建芳². 未知环境下基于可拓遗传算法的避障算法[J]. 计算机工程与应用, 2010, 46(20): 226-229.

WANG Yue-chao¹，SHEN Jian-fang². Obstacle-avoiding algorithm based on extension genetic algorithm in unknown environment[J]. Computer Engineering and Applications, 2010, 46(20): 226-229.

[1]	谢蓝¹，曾韬²，余永权¹，施景霞¹. 可拓检测的可拓变换机理[J]. 计算机工程与应用, 2011, 47(5): 149-151.
[2]	黄金才,陈文伟. 可拓数据挖掘的概念与理论 [J]. 计算机工程与应用, 2006, 42(14期): 7-.

未知环境下基于可拓遗传算法的避障算法

Obstacle-avoiding algorithm based on extension genetic algorithm in unknown environment

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