[1]蔡文彬,朱庆保.未知环境下基于快速搜索随机树的机器人路径滚动规划[J].南京师范大学学报(工程技术版),2009,09(02):079-83.
 Cai Wenbin,Zhu Qingbao.Rolling Path Planning of Robot Based on Rapidly Exploring Random Tree in an Unknown Environment[J].Journal of Nanjing Normal University(Engineering and Technology),2009,09(02):079-83.
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未知环境下基于快速搜索随机树的机器人路径滚动规划
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南京师范大学学报(工程技术版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
09卷
期数:
2009年02期
页码:
079-83
栏目:
出版日期:
2009-06-30

文章信息/Info

Title:
Rolling Path Planning of Robot Based on Rapidly Exploring Random Tree in an Unknown Environment
作者:
蔡文彬;朱庆保;
南京师范大学计算机科学与技术学院, 江苏南京210097
Author(s):
Cai WenbinZhu Qingbao
School of Computer Sciences,Nanjing Normal University,Nanjing 210097,China
关键词:
移动机器人 滚动规划 快速搜索随机树 未知环境
Keywords:
mob ile robot rolling p lan rapid ly exp lor ing random tree unknown env ironm ent
分类号:
TP242
摘要:
在未知环境下,移动机器人没有全局信息,一次只能规划出探测范围内的局部路径.针对这一特点,提出了一种全新的基于滚动窗口的快速搜索随机树算法.该算法以机器人出发点为根节点,充分利用机器人实时测得的局部环境信息,以滚动方式进行在线扩展,逐渐增加叶节点直至随机树的叶节点包括了目标节点,从根节点到目标节点的随机树的边即为规划出的路径.大量仿真实验表明,即使在障碍物非常复杂的未知地理环境下,该算法也能快速规划出一条全局优化路径,且能安全避障.
Abstract:
In a com plex unknown env ironm ent, m ob ile robo t doesn t’ ow n g loba l in fo rm ation so that it can on ly make a p lan abou t the loca l path w hich falls into its detec tab le a rea. In a llusion to the feature, a new rap idly explo ring random tree algor ithm for pa th planning is pu t forwa rd to plan an optima l path for mob ile robo t, wh ich is based on rolling w indow. A ccording to the algor ithm, the start-po int of them obile robot is regarded to be the root node. Besides, fu ll use is m ade o f loca l env ironm en tal inform ation detected by the robot to expand the space in a ro lling on- line sty le and add a new node to a random tree until the leaf node o f the tree conta ins the ta rget node. The edg es of the random tree composed o f the route from the in itia l node to the target node a re just the pa th where the robot w alks by. The sim ulation results illustrate that the proposed algorithm can be used to so lve the path plann ing for mob ile robot even in the com plex unknown environm ent, and the successful obstac le avo idance is a lso ach ieved.

参考文献/References:

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备注/Memo

备注/Memo:
基金项目: 国家自然科学基金( 60673102)和江苏省自然科学基金( BK2006218)资助项目.
通讯联系人: 朱庆保, 教授, 博士生导师, 研究方向: 人工智能与智能控制. E-m ail:zhuq ingbao@ n jnu. edu. cn
更新日期/Last Update: 2013-04-23