[1]蒲兴成,张军,张毅.基于神经网络的改进行为协调控制及其在智能轮椅路径规划中的应用[J].智能系统学报,2011,6(05):456-463.
 PU Xingcheng,ZHANG Jun,ZHANG Yi.Modified behavior coordination for intelligent wheelchair path planning based on a neural network[J].CAAI Transactions on Intelligent Systems,2011,6(05):456-463.
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基于神经网络的改进行为协调控制及其在智能轮椅路径规划中的应用(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第6卷
期数:
2011年05期
页码:
456-463
栏目:
出版日期:
2011-10-30

文章信息/Info

Title:
Modified behavior coordination for intelligent wheelchair path planning based on a neural network
文章编号:
1673-4785(2011)05-0456-08
作者:
蒲兴成1张军2张毅2
1.重庆邮电大学 数理学院,重庆 400065;
2.重庆邮电大学 自动化学院,重庆 400065
Author(s):
PU Xingcheng1 ZHANG Jun2 ZHANG Yi2
1.Mathematics and Physics College, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;
2.Automation College, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
关键词:
机器人智能轮椅非结构化环境路径规划神经网络行为协调控制器
Keywords:
robot intelligent wheelchair unstructured environment path planning neural network behavior coordination control
分类号:
TP24
文献标志码:
A
摘要:
针对传统的基于行为的智能轮椅的路径规划方法在室外非结构环境下的路径规划效果差的问题,提出一种新的智能轮椅的路径规划算法.该算法利用模糊逻辑设计了基本控制行为,并在此基础上结合大量实际经验使用神经网络设计了行为协调控制器.改进的算法将仲裁机制和命令融合机制2种行为协调方法有效结合起来,并吸收了这2种行为协调方法的优点,从而改善了系统的反应速度,极大提高了控制精确;另一方面,该算法还可以识别陷阱区域并通过自主改变行为的权重方法控制轮椅逃出陷阱区域,因而具备了较强的人工智能特征.仿真和实物实验验证了该算法智能性高且实现简单,适用于室外非结构化环境下的机器人路径规划.
Abstract:
In order to solve the poor effects of traditional behaviorbased path planning of intelligent wheelchairs in an outdoor unstructured environment, a new path planning method was proposed in this paper. The new algorithm uses fuzzy logic to design basic control behavior, and on this basis applies a neural network to design behavior coordination by combining a large amount of practical experience. The improved algorithm can combine arbitration mechanisms with fusion mechanisms successfully; it absorbs the major advantage of these two original algorithms and improves response speed of the system while enhancing the control accuracy significantly. On the other hand, the method can identify trap area and control the wheelchair escape from the trap by changing the behavior weights independently, therefore displaying strong artificial intelligence characteristics. The simulation and real experimental results verify that the algorithm is capable of advanced intelligence and can be implemented easily. Additionally, it can be used in an outdoor unstructured environment for robot path planning.

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备注/Memo

备注/Memo:
收稿日期: 2011-01-16.
基金项目:科技部国际合作资助项目(2010DFA12160);重庆市科委资助项目(CSCT,2010AA2055);重庆邮电大学青年基金资助项目(A200950).
通信作者:蒲兴成.E-mail:puxingcheng@sina.com.
作者简介:
蒲兴成,男,1973年生,副教授,博士,主要研究方向为非线性系统、随机系统和智能控制等.主持和参与省部级基金项目8项,发表学术论文40余篇,出版学术专著1部、教材1部.
张军,男,1985年生,硕士研究生,主要研究方向为人工智能和机器人控制.
张毅,男,1966年生,教授,博士生导师,中国人工智能学会理事、青年工作委员会副主任、智能机器人专业委员会委员,中国计量测试学会高级会员,《机器人技术及其应用》杂志理事.主要研究方向为智能服务机器人、信息无障碍技术、智能人机交互技术.申请国家发明专利20项,获得国家发明专利10项,发表学术论文150余篇,其中被SCI、EI、ISTP检索80余篇,出版专著2部,撰写教材3部.
更新日期/Last Update: 2011-11-16