广东工业大学 信息工程学院,广东,广州,510006
揭云飞(1994–),男,硕士研究生,主要研究方向为室内定位技术
王峰(1961–),男,教授,博士,主要研究方向为卫星导航、机器人和车辆建模及控制、室内定位技术,E-mail:everett.wang@gdut.edu.cn
网络首发:2020-09-17,
纸质出版:2020
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揭云飞, 王峰, 钟有东, 智凯旋, 熊超伟. 基于地面特征的单目视觉机器人室内定位方法[J]. 广东工业大学学报, 2020, 37(5): 31-37.
Jie Yun-fei, Everett Wang, Zhong You-dong, et al. An Indoor Positioning Method of Monocular Vision Robot Based on Floor Features[J]. 2020, 37(5): 31-37.
揭云飞, 王峰, 钟有东, 智凯旋, 熊超伟. 基于地面特征的单目视觉机器人室内定位方法[J]. 广东工业大学学报, 2020, 37(5): 31-37. DOI: 10.12052/gdutxb.190143.
Jie Yun-fei, Everett Wang, Zhong You-dong, et al. An Indoor Positioning Method of Monocular Vision Robot Based on Floor Features[J]. 2020, 37(5): 31-37. DOI: 10.12052/gdutxb.190143.
针对高精度的机器人室内定位方法中成本过高的问题
提出一种基于地面特征的单目视觉机器人室内定位方法。该方法通过安装在机器人底盘的单目鱼眼摄像头采集地面图片
并经过一系列图像处理
将得到的地面方格直线和相机的位姿关系作为观测量
通过推导出观测方程并根据扩展卡尔曼滤波算法得到机器人的位置信息。基于机器人当前时刻位置数据和地面的固定方格大小提出线预测算法
有效地排除干扰线段的影响。实验结果表明
该机器人室内定位方法定位精度可以达到2 cm
具有较好的鲁棒性
能够为低成本的机器人室内定位提供较好的技术参考。
In order to solve the problem of high cost in high-precision robot indoor positioning method
an indoor positioning method based on ground features for monocular vision robot is proposed. This method collects the ground image through the monocular fisheye camera installed on the robot chassis
and after a series of image processing
the relationship between the ground grid straight line and the pose of the camera is used as the observational measurements
then the position information of the robot is obtained by deriving the observation equation and the extended Kalman filter algorithm. Based on the current time position data of the robot and the fixed square size of the ground
a line prediction algorithm is proposed to effectively eliminate the influence of the interference line segment. The experimental results show that the positioning accuracy of the robot indoor positioning method can reach 2 cm
which has good robustness and also can provide a good technical reference for low-cost robot indoor positioning.
SONG K N, WANG B, TANG C Y. Research on indoor localization method based on laser ranging scanning [J]. Laser Infrared, 2016, 46(8): 938-942.
HESS W, KOHLER D, RAPP H, et al. Real time loop closure in 2D LIDAR SLAM[C]//2016 IEEE International Conference on Robotics and Auto- mation (ICRA), Computer Science. Stockholm: IEEE, 2016: 1271-1278.
MICUSIK B, WILDENAUER H. Descriptor free visual indoor localization with line segments[C]// 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston. MA: IEEE, 2015: 3165-3173.
DONG X L, YUAN J, ZHANG X B, et al . Mobile robot global localization based on topological relationship between image sequences in indoor environments [J ] . ROBOT, 2019, 41(1): 83-94.
CHANG J M, WANG H L. Research on location fingerprint database filtering algorithm in indoor location system [J]. Modern Electronic Technique, 2019, 42(17): 10-13.
YANG B, ZHANG P F, LI J J, et al . An indoor positioning and navigation technology based on bluetooth [J ] . Science of Surveying and Mapping, 2019, 44(6): 89-95.
SŁAWOMIR R, AMBROZIAK L, ZDZISŁAW G, et al. Real time localization system with extended Kalman filter for indoor applications[C]//2016 21st International Conference on Methods and Models in Automation and Robotics (MMAR), Robotics. Miedzyzdroje: IEEE, 2016: 42-47.
ZHENG L, TAO Q. Implementation of self-calibration and distortion correction [J]. Computer Engineering, 2016, 42(9): 252-256.
XIAO F, WU Z, HUANG Z D, et al. Indoor robot visual positioning system based on floor features[C]//2018 3rd International Conference on Robotics and Automation Engineering (ICRAE), Mobile Robots and Autonomous Systems. Guangzhou: IEEE, 2018: 97-101.
MARTIN A, FISCHLER, BOLLES, et al . Random sample consensus: a paradigm for model fitting with applications to image analysis and automat cartography [J ] . Communications of the ACM, 1981, 24: 381-395.
PETKOVIĆ T, LONČARIĆ S. Using gradient orientation to improve least squares line fitting[C]//2014 Canadian Conference on Computer and Robot Vision (CRV), Real-time Sensing and Control. Montreal: IEEE, 2014: 226-231.
ZHANG Y L. Research on fitting lines based on least squares method [J]. Information Communications, 2014(11): 44-45.
VENTOSA S, SIMON C, SCHIMMEL M, et al . The S-Transform from a wavelet point of view [J ] . IEEE Transactions on Signal Processing, 2008, 56(7): 2771-2780.
MA L, JIANG W W, ZHANG X X. Single Passive location algorithm based on improved extended Kalman filter [J]. Computer Engineering and Applications, 2016, 52(10): 124-127.
MA X D, ZENG B, YE L F. An improved visual Odometry/SINS integrated localization algorithm based on BA [J]. Journal of Guangdong University of Technology, 2017, 34(6): 32-36.
GUO P Z, HU G, FU H. Research on path planning with random time for vehicle navigation [J]. Journal of Guangdong University of Technology, 2012, 29(1): 35-38.
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