[1]薛英花,田国会,吴 皓,等.智能空间中的服务机器人路径规划[J].智能系统学报,2010,5(03):260-265.
 XUE Ying-hua,TIAN Guo-hui,WU Hao,et al.Path planning for service robots in an intelligent space[J].CAAI Transactions on Intelligent Systems,2010,5(03):260-265.
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第5卷
期数:
2010年03期
页码:
260-265
栏目:
出版日期:
2010-06-25

文章信息/Info

Title:
Path planning for service robots in an intelligent space
文章编号:
1673-4785(2010)03-0260-06
作者:
薛英花12 田国会2 吴 皓1吉艳青1
1.山东大学 控制科学与工程学院,山东 济南 250061;
2.山东财政学院 计算机信息工程学院,山东 济南 250014
Author(s):
XUE Ying-hua12 TIAN Guo-hui1 WU Hao1 JI Yan-qing1
1.School of Control Science and Engineering, Shandong University, Ji’nan 250061, China;
 2.School of Computer and Information Engineering, Shandong Finance Institute, Ji’nan 250014, China
关键词:
智能空间服务机器人路径规划危险度地图粒子群优化算法A*算法
Keywords:
intelligent space service robot path planning danger degree map particle swarm optimization A* algorithm
分类号:
TP24
文献标志码:
A
摘要:
为了加深服务机器人对环境的理解,实现安全高效的智能空间导航,建立了一种信息更为丰富的环境模型——危险度地图;并针对智能空间环境部分未知的特点,设计了分层的路径规划方法.静态规划层根据已知环境信息,采用改进的粒子群优化算法规划初始最优路径,动态规划层利用基于动态危险度地图的改进A*算法进行避障.该方法克服了常规算法只追求路径最短的缺点,增加了对路径危险度的评价,规划出的路径既安全又较短;且该方法实现简单,实时性好.仿真结果验证了该方案的可行性.
Abstract:
A service robot must be capable of deeply understand its environment, so that it may safely navigate intelligent spaces with high performance. In order for this to be possible, a new environmental model, or danger degree map (DDM), was created to provide enriched environmental information for service robots. As the intelligent space is partly unknown, the layered path planning method was used. A modified particle swarm optimization (PSO) algorithm based on a known environment was introduced to get a static optimized path. The dynamic layer used a modified A* algorithm for avoidance of dynamic obstacles on the basis of the dynamic DDM. The proposed method adds evaluation of the degree of danger in a path to overcome the disadvantages of conventional methods, which follow the shortest path and ignore safety. The new method is simple and meets the realtime requirements of robot navigation. The resulting dynamic path is not only safe enough but also comparatively short. Simulation results demonstrated the feasibility of the method. 

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2009-12-15.
基金项目:国家“863”计划重点资助项目(2006AA040206);国家“863”计划资助项目
通信作者:薛英花.
E-mail:yhua_xue@yahoo.com.cn.
作者简介: 薛英花,女,1974年生,博士研究生、讲师.主要研究方向为智能空间、机器人路径规划、机器人物品搜寻与管理.先后参加了国家自然科学基金、国家“863”计划等多项项目,发表学术论文10余篇.
田国会,男,1969年生,教授、博士生导师.山东大学重要岗位教授、控制科学与工程学院副院长、中国人工智能学会理事、山东省自动化学会理事.主要研究方向为服务机器人、智能空间、多机器人系统的协调与协作、现代物流系统的优化与调度等.作为课题负责人或执行负责人已完成国家自然科学基金项目、国家“863”计划CIMS主题基金项目、国防预研项目、中国博士后科学基金项目、山东省自然科学基金项目等12项.获山东省科技进步二等奖、山东省教委科技进步(自然科学理论)一等奖各1项.发表学术论文80余篇.
 吴 皓,女,1972年生,博士研究生、副教授.主要研究方向为多机器人系统的协调与协作、智能空间中的机器人定位导航.先后参加了国家自然科学基金项目、国家“863”计划等多项项目,发表学术论文10余篇.
更新日期/Last Update: 2010-08-27