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浙江大学学报(工学版)
J4  2010, Vol. 44 Issue (2): 253-258    DOI: 10.3785/j.issn.1008-973X.2010.02.008
计算机技术﹑电信技术     
基于模糊评价的未知环境地图构建探测规划
王立, 熊蓉, 褚健, 刘勇
（浙江大学 工业控制技术国家重点实验室,浙江 杭州 310027）
Fuzzy evaluation based exploring planning for map building in unknown environment
WANG Li, XIONG Rong, CHU Jian,LIU Yong
(State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China)
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摘要：

针对未知环境信息的模糊性和不确定性,提出基于模糊综合评价决策的机器人未知环境地图构建自主探测规划方法.该方法将栅格图中的介于已知区域和未知区域边缘的前沿点按距离和可行性进行分类,选取优先级较高的类别中的点作为候选点.根据候选点与当前位置的距离、信息增益和可定位性进行模糊综合评价,以较小的计算代价决定机器人下一步的探测位姿或者某一段路径上的一系列探测位姿,从而完成对未知区域的探测,构建出准确度高的环境栅格图和特征线段图.仿真实验结果表明,该方法提高了自主探测效率,并具有很高的实时性.
Abstract:

A fuzzy evaluation based approach was proposed to solve the exploring problem for autonomous robotic mapping in unknown environment to deal with the fuzziness and uncertainty of unknown environmental information. The approach classified the frontiers which were between the known and unknown areas of grid map according to their distance and feasibility, and then chose the points with higher priority as candidates. Distances between the candidate points and current position, information gains and localizability were evaluated in fuzzy rules. The selection of the next observing pose or a series of next poses in path was achieved in low computational cost with the fuzzy evaluation. Then the exploration was finished, and the grid map and the feature map were accurately constructed. Experimental results demonstrate that the approach can improve the efficiency of exploring and achieve high performance in real-time planning.
出版日期: 2010-03-09
:  TP 242.6  
基金资助:

国家自然科学基金资助项目（60675049);国家“863”高技术研究发展计划资助项目(2008AA04Z209)；浙江省自然科学基金资助项目（Y106414)；中央高校基本科研业务专项资金资助项目(2009QNA5004).
通讯作者: 熊蓉，女，副教授.     E-mail: rxiong@iipc.zju.edu.cn
作者简介: 王立（1983—）, 女，湖南长沙人，博士生，从事智能机器人的研究.
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王立, 熊蓉, 褚健, 等. 基于模糊评价的未知环境地图构建探测规划[J]. J4, 2010, 44(2): 253-258.

WANG Li, XIONG Rong, CHU Jian, et al. Fuzzy evaluation based exploring planning for map building in unknown environment. J4, 2010, 44(2): 253-258.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2010.02.008    或    http://www.zjujournals.com/eng/CN/Y2010/V44/I2/253

［1］ THRUN S. Robotic mapping: a survey. exploring artificial intelligence in the new millenium［M］. San Francisco: Morgan Kaufmann, 2002: 1-35.
［2］ ISIER V, KANNAN S, DANIILIDIS K. Local exploration: online algorithms and a probabilistic framework［C］//Proceedings of the 2003 IEEE International Conference on Roboticsand Automation. USA:IEEE, 2003:1913-1920.
［3］ YAMAUCHI B. A frontier-based approach for autonomous exploration［C］//Proceedings of the IEEE International Symposium on Computational Intelligence in Robotics and Automation. Monterey, CA: IEEE, 1997: 146-151.
［4］ TOVAR B, MURRIETA-CID R, ESTEVES C. Robot motion planning for map building［C］//Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems.Lausanne, Switzerland: IEEE, 2002:673-680.
［5］ FREDA L, ORIOLO G. Frontier-based probabilistic strategies for sensor-based exploration［C］//Proceedings of the 2005 IEEE International Conference on Robotics and Automation. Barcelona, Spain: IEEE, 2005: 2892-3898.
［6］ GONZLEZ-BAOS H, EFRAT A, LATOMBE J C, et al. Planning robot motion strategies for efficient model construction ［C］// The 9th International Symposium on RoboticsResearch. Salt Lake City, UT: Springer-Verlag, 1999: 345-352.
［7］ GONZLEZ-BAOS H H, LATOMBE J C. Navigation strategies for exploring indoor environments ［J］. International Journal of Robotics Research, 2002, 21(10): 829-848.
［8］ MAKARENKO A A, WILLIAMS S B, BOURGAULT F, et al. An experiment in integrated exploration［C］//Proceedings of IEEE/RSJ International Conference on Intelligent Robots andSystems. Lausanne, Switzerland: IEEE, 2002: 534-539.
［9］ 张恒,樊晓平.移动机器人同步定位与地图构建过程中的轨迹规划研究［J］.机器人,2006,28(3):285-290.
ZHANG Heng, FAN Xiao-ping. Mobile robot trajectory planning in simultaneous localization and mapping problem ［J］.Robot, 2006, 28(3): 285-290.
［10］ MACKAY D. Bayesian methods for adaptive models ［D］. Pasadena: California Institute of Technology, 1991.
［11］ 周光明,贾梦雷,陈宗海.移动机器人未知环境自主探测的一种高效算法［J］.上海交通大学学报,2005,39(6): 936-940.
ZHOU Guang-ming, JIA Meng-lei, CHEN Zong-hai. An efficient algorithm for mobile robot’s autonomous exploration in unknown environments ［J］.Journal of Shanghai JiaotongUniversity, 2005, 39(6): 936-940.
［12］ STACHNISS C, GRISETTI G, BURGARD W. Information gain-based exploration using rao-blackwellized particle filters［C］// Proceedings of Robotics: Science and Systems.Cambridge, UK: ［s.n.］,2005: 65-72.
［13］ 熊蓉,褚健,吴俊.基于点线相合的机器人增量式地图构建［J］.控制理论与应用,2007,24(2):170-176.
XIONG Rong, CHU Jian, WU Jun. Incremental mapping based on dot-line congruence for robot［J］.Control Theory and Applications, 2007,24(2):170-176.
［14］ DECHTER R, PEARL J. Generalized best-first search strategies and the optimality of A*［J］. Journal of the ACM, 1985, 32(3): 505-536.
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