基于2维激光雷达的小型地面移动机器人自主回收方法

doi:10.13973/j.cnki.robot.2017.0688

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李捷, 袁夏, 赵春霞, 陆建峰. 基于2维激光雷达的小型地面移动机器人自主回收方法[J]. 机器人, 2017, 39(5): 688-696.DOI: 10.13973/j.cnki.robot.2017.0688. LI Jie, YUAN Xia, ZHAO Chunxia, LU Jianfeng. Automatic Withdrawal Method Based on 2D Laser Radar for Small Ground Mobile Robot. ROBOT, 2017, 39(5): 688-696. DOI: 10.13973/j.cnki.robot.2017.0688.

摘要为了解决小型地面移动机器人在野外环境中的回收问题，利用2维激光雷达进行环境感知与末端精确引导，设计并实现了一个自主回收系统．首先，提出一种自适应曲率滤波算法预先对雷达数据进行滤波处理．然后，在检测引导目标过程中，结合基于密度和最近邻度量方法对散乱的数据进行聚类，并且利用引导目标和辅助目标之间的几何结构约束进行目标检测与匹配．最后，采用基于影响层划分和候选方向评估的方法进行实时避障与最优行驶方向选择，对机器人进行精确引导，从而实现机器人的自主回收．在野外环境中对该自主回收系统进行验证，对自主回收系统中的若干环节分别进行实验分析．实验结果表明，该方法能够有效地实现小型地面移动机器人在野外环境中的自主回收．

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	李捷
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关键词 ：移动机器人, 自主回收, 2维激光雷达, 精确引导, 目标检测

Abstract：In order to resolve the withdrawal problem of small ground mobile robots in natural environment, the 2D laser radar is used for environmental perception and terminal precise navigation, and an automatic withdrawal system is designed and implemented. Firstly, an adaptive curvature filtering algorithm is proposed to process the radar data in advance. Then, the scattered data is clustered in the process of detecting the guiding target according to the density and the nearest neighbor measurement. The target detection and matching are carried out by using the geometric structure constraint between the guiding target and the auxiliary target. Finally, the real-time obstacle avoidance and the optimal forward direction selection are conducted based on the method of affected layer division and candidate direction estimation. Thus the robot is accurately guided to accomplish automatic withdrawal. The automatic withdrawal system is validated in natural environment. And some aspects of the automatic withdrawal system are analyzed experimentally. Experimental results show that the proposed method can effectively accomplish the automatic withdrawal of the small ground mobile robot in natural environment.

Key words： mobile robot automatic withdrawal 2D laser radar precise navigation target detection

收稿日期: 2017-03-27 录用日期: 2017-05-18

TP24

基金资助:国家自然科学基金青年基金（61603184）；核高基国家重点专项（2015ZX01041101）；江苏省社会安全图像与视频理解重点实验室创新基金（30916014107）；江苏省自然科学基金青年基金（BK20140794）

通讯作者: 袁夏,yuanxia@njust.edu.cn E-mail: yuanxia@njust.edu.cn

作者简介: 李捷(1988-),男,博士生.研究领域:智能机器人环境理解,计算机视觉,RGB-D图像显著性分析.
袁夏(1981-),男,博士,副教授.研究领域:地面智能机器人环境理解与自主导航技术,3维彩色点云数据分析,RGB-D图像显著性分析.
赵春霞(1964-),女,教授,博士生导师.研究领域:智能机器人与智能检测系统,计算机视觉,环境理解与建模,智能交通管理.

链接本文:

https://robot.sia.cn/CN/10.13973/j.cnki.robot.2017.0688 或 https://robot.sia.cn/CN/Y2017/V39/I5/688

[1] 李磊,叶涛,谭民,等.移动机器人技术研究现状与未来[J].机器人,2002,24(5):475-480. Li L, Ye T, Tan M, et al. Present state and future development of mobile robot technology research[J]. Robot, 2002, 24(5):475-480.
[2] 徐国保,尹怡欣,周美娟.智能移动机器人技术现状及展望[J].机器人技术与应用,2007(2):29-34. Xu G B, Yin Y X, Zhou M J. The present situation and future of intelligent mobile robot technologies[J]. Robot Technique and Application, 2007(2):29-34.
[3] 杨成宏.面向智能清扫机器人的路径规划技术研究[D].南京:南京理工大学,2012. Yang C H. Research on path planning technology for intelligent cleaning robots[D]. Nanjing:Nanjing University of Science and Technology, 2012.
[4] 郝宗波,洪炳镕.室内环境下移动机器人自主充电研究[J].哈尔滨工业大学学报,2005,37(7):885-887. Hao Z B, Hong B R. Research on auto-recharging for mobile robot in indoor environment[J]. Journal of Harbin Institute of Technology, 2005, 37(7):885-887.
[5] Hofner C, Schmidt G. Path planning and guidance techniques for an autonomous mobile cleaning robot[J]. Robotics and Autonomous Systems, 1995, 14(2/3):199-212.
[6] 肖潇.未知环境下移动机器人自主搜索技术研究[D].天津:南开大学,2006. Xiao X. Autonomous search technology for mobile robots under unknown environment[D]. Tianjin:Nankai University, 2006.
[7] 张志广.基于坦克式移动机器人定位和路径规划技术研究[D].长沙:国防科学技术大学,2005. Zhang Z G. Studies on technology of localization and path planning based on tank mobile robots[D]. Changsha:National University of Defense Technology, 2005.
[8] Li W, Wu H, Chen Y, et al. Autonomous navigation experiment for mobile robot based on IHDR algorithm[C]//IEEE International Conference on Cyber Technology. Piscataway, USA:IEEE, 2015:572-576.
[9] 欧青立,何克忠.室外智能移动机器人的发展及其关键技术研究[J].机器人,2000,22(6):519-526. Ou Q L, He K Z. Research on key techniques and development of outdoor intelligent autonomous mobile robot[J]. Robot, 2000, 22(6):519-526.
[10] 庄秀华.基于单线激光雷达的障碍物检测与跟踪研究[D].长沙:湖南大学,2014. Zhuang X H. Research on obstacle detection and tracking based on the single laser radar[D]. Changsha:Hunan University, 2014.
[11] 王洪涛.基于北斗卫星导航系统的移动机器人定位技术及应用[D].哈尔滨:哈尔滨工程大学,2014. Wang H T. Based on BeiDou satellite navigation system of mobile robot localization technology and application[D]. Harbin:Harbin Engineering University, 2014.
[12] 肖辰彬.GPS/BD-DR组合导航系统优化设计与实现[D].成都:西南交通大学,2014. Xiao C B. Optimized design & implementation of GPS/BD-DR integrated navigation system[D]. Chengdu:Southwest Jiaotong University, 2014.
[13] 郑平方,常青,张其善,等.车载GPS/DR组合导航系统的研究[J].北京航空航天大学学报,1999,25(5):513-516. Zheng P F, Chang Q, Zhang Q S, et al. Study of GPS/DR integrated navigation system for vehicle[J]. Journal of Beijing University of Aeronautics and Astronautics, 1999, 25(5):513-516.
[14] 孟祥荔.基于GPS定位的移动机器人导航系统的研究[D].天津:天津理工大学,2007. Meng X L. Research on navigation system of mobile robot based on GPS positioning[D]. Tianjin:Tianjin University of Technology, 2007.
[15] 于金霞,蔡自兴,段琢华.基于激光雷达的移动机器人运动目标检测与跟踪[J].电子器件,2007,30(6):327-332. Yu J X, Cai Z X, Duan Z H. Detection and tracking of moving object with a mobile robot using laser scanner[J]. Chinese Journal of Electron Devices, 2007, 30(6):327-332.
[16] Gong Y H. Spectrally regularized surfaces[D]. Zurich, Switzerland:Eidgenossische Technische Hochschule Zurich, 2015.
[17] Yang Y, He H, Xu G. Adaptively robust filtering for kinematic geodetic positioning[J]. Journal of Geodesy, 2001, 75(2):109-116.
[18] 王雨晨.移动机器人运动目标检测与跟踪[D].杭州:浙江工业大学,2015. Wang Y C. Detection and tracking of moving object with a mobile robot[D]. Hangzhou:Zhejiang University of Technology, 2015.
[19] Rodriguez A, Laio A. Clustering by fast search and find of density peaks[J]. Science, 2014, 344(6191):1492-1496.
[20] 蔡自兴,郑敏捷,邹小兵.基于激光雷达的移动机器人实时避障策略[J].中南大学学报:自然科学版,2006,37(2):324-329. Cai Z X, Zheng M J, Zou X B. Real-time obstacle avoidance for mobile robots strategy based on laser radar[J]. Journal of Central South University:Science and Technology, 2006, 37(2):324-329.
[21] 郑敏捷,蔡自兴,于金霞.一种动态环境下的移动机器人避障策略[J].高技术通讯,2006,16(8):813-819. Zheng M J, Cai Z X, Yu J X. An obstacle avoidance strategy of mobile robots under dynamic environments[J]. Chinese High Technology Letters, 2006, 16(8):813-819.
[22] Zhang D L, Wu H Y, Chen Y, et al. Escaping from obstacle zone for mobile robot based on maximum distance priority mechanism[C]//Chinese Automation Congress. Piscataway, USA:IEEE, 2015:336-341.