一种用于图像特征提取的改进ORB-SLAM算法
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摘要
针对复杂室内环境下视觉SLAM定位存在实时性差、轨迹漂移等问题,本文提出了一种基于图像特征提取方法的ORBSLAM算法。该算法在前端中提高图像特征检测与匹配的效率和精度,引入闭环检测策略优化相机位姿轨迹,提高定位精度。以不同来源图像对比分析不同特征提取算法SIFT、SURF、ORB的有效性,运用该算法估计机器人运动轨迹,与真实轨迹相对位姿误差为0.144 8 m,试验表明所提出的方法切实可行,具有较高的稳健性。
Aiming at the problem of poor real-time performance and trajectory drift in visual SLAM positioning in complex indoor environments,this paper proposes an ORB-SLAM algorithm based on image feature detection extraction method. The algorithm improves the efficiency and accuracy of image feature detection and matching in the front-end,introduces a closed-loop detection strategy to optimize camera pose trajectory,and improves positioning accuracy. The SIFT,SURF and ORB of different feature extraction algorithms are compared and analyzed in different sources. The robot motion trajectory is estimated by this algorithm. The relative pose error from the real trajectory is 0.144 8 m. Experiments show that the proposed method is feasible and robustness.
Aiming at the problem of poor real-time performance and trajectory drift in visual SLAM positioning in complex indoor environments,this paper proposes an ORB-SLAM algorithm based on image feature detection extraction method. The algorithm improves the efficiency and accuracy of image feature detection and matching in the front-end,introduces a closed-loop detection strategy to optimize camera pose trajectory,and improves positioning accuracy. The SIFT,SURF and ORB of different feature extraction algorithms are compared and analyzed in different sources. The robot motion trajectory is estimated by this algorithm. The relative pose error from the real trajectory is 0.144 8 m. Experiments show that the proposed method is feasible and robustness.
引文
[1]毕京学,汪云甲,曹鸿基,等.一种基于全向指纹库的Wi Fi室内定位方法[J].测绘通报,2018(2):25-29.
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[10]RUBLEE E,RABAUD V,KONOLIGE K,et al.ORB:an efficient alternative to SIFT or SURF[C]∥IEEEInternational Conference on Computer Vision.Ontario,Canada:IEEE,2012:2564-2571.
[11]许晓东,陈国良,李晓园,等.一种采用图像特征匹配技术的RGB-D SLAM算法[J].测绘通报,2017(10):48-51.
[12]MUR-ARTAL R,MONTIEL J M M,TARDS J D.ORB-SLAM:a versatile and accurate monocular SLAMsystem[J].IEEE Transactions on Robotics,2015,31(5):1147-1163.
[13]王丽佳.基于图优化的单目视觉SLAM技术研究[D].武汉:华中科技大学,2016.
[14]公维思,周绍磊,吴修振,等.基于改进FAST特征检测的ORB-SLAM方法[J].现代电子技术,2018(6):53-56.
[15]余杰.基于ORB关键帧闭环检测算法的SLAM方法研究[D].杭州:浙江工业大学,2016.
[16]章园媛.单目视觉自主移动机器人同步定位与地图构建技术[D].哈尔滨:哈尔滨工业大学,2009.
[2]DAVISON A J.Real-time simultaneous localisation and mapping with a single camera[C]∥Proceedings of IEEE International Conference on Computer Vision.Nice,France:IEEE,2003:1403.
[3]DAVISON A J,REID I D,MOLTON N D,et al.Mono SLAM:real-time single camera SLAM[J].IEEE Transactions on Pattern Analysis&Machine Intelligence,2007,29(6):1052-1067.
[4]ZHU D X.Binocular vision-SLAM using improved SIFTalgorithm[C]∥Proceedings of the 2nd International Workshop on Intelligent Systems and Applications(ISA).Wuhan,China:IEEE,2010:1-4.
[5]HENRY P,KRAININ M,HERBST E,et al.RGB-Dmapping:using depth cameras for dense 3D modeling of indoor environments[C]∥Experimental Robotics.Berlin Heidelberg:Springer.2014:647-663.
[6]顾照鹏,刘宏.单目视觉同步定位与地图创建方法综述[J].智能系统学报,2015,10(4):499-507.
[7]高翔,张涛等.视觉SLAM十四讲:从理论到实践[M].北京:电子工业出版社,2017.
[8]LOWE D G.Distinctive image features from scale-invariant keypoints[J].International Journal of Computer Vision,2004,60(2):91-110.
[9]BAY H,ESS A,TUYTELAARS T,et al.Speeded-up robust features(SURF)[J].Computer Vision&Image Understanding,2008,110(3):346-359.
[10]RUBLEE E,RABAUD V,KONOLIGE K,et al.ORB:an efficient alternative to SIFT or SURF[C]∥IEEEInternational Conference on Computer Vision.Ontario,Canada:IEEE,2012:2564-2571.
[11]许晓东,陈国良,李晓园,等.一种采用图像特征匹配技术的RGB-D SLAM算法[J].测绘通报,2017(10):48-51.
[12]MUR-ARTAL R,MONTIEL J M M,TARDS J D.ORB-SLAM:a versatile and accurate monocular SLAMsystem[J].IEEE Transactions on Robotics,2015,31(5):1147-1163.
[13]王丽佳.基于图优化的单目视觉SLAM技术研究[D].武汉:华中科技大学,2016.
[14]公维思,周绍磊,吴修振,等.基于改进FAST特征检测的ORB-SLAM方法[J].现代电子技术,2018(6):53-56.
[15]余杰.基于ORB关键帧闭环检测算法的SLAM方法研究[D].杭州:浙江工业大学,2016.
[16]章园媛.单目视觉自主移动机器人同步定位与地图构建技术[D].哈尔滨:哈尔滨工业大学,2009.