Abstract：SeqSLAM is a widely used loop closure detection algorithm in mobile robot and autonomous vehicle field. It could recognize revisited places by comparing sequences of images even under dramatic changes of season, illumination, and weather. However, SeqSLAM is vulnerable to viewpoint changes. In addition, SeqSLAM compares sequences of images by brute force method, which prevents its real-time application to large-scale image datasets. To address these problems, we first represent each image by a kind of low dimensional description — vector of locally aggregated descriptors (VLAD) which is robust to viewpoint changes, and then replace the brute force method by an approximate nearest neighbor search algorithm — hierarchical navigable small world graphs (HNSW). Tests on publicly available datasets show that, the improved SeqSLAM with VLAD and HNSW could obtain much better detection results in the respect of precision-recall evaluation and the search time is reduced by orders of magnitude. We make code publicly available at https://github.com/qipengliuNTU/Efficient-SeqSLAM-with-HNSW.
张梦真, 王庆芝, 刘其朋. 基于层次化可导航小世界网络改进的SeqSLAM算法[J]. 复杂系统与复杂性科学, 2023, 20(1): 105-110.
ZHANG Mengzhen, WANG Qingzhi, LIU Qipeng. Improved SeqSLAM Using Hierarchical Navigable Small World Graphs. Complex Systems and Complexity Science, 2023, 20(1): 105-110.
[1] CADENA C, CARLONE L, CARRILLO H, et al. Past, present, and future of simultaneous localization and mapping: toward the robust-perception age[J]. IEEE Transactions on Robotics, 2016, 32(6): 13091332. [2] 王霞,左一凡. 视觉SLAM研究进展[J]. 智能系统学报, 2020, 15(5): 825834. WANG X, ZUO Y F. Advances in visual SLAM research[J]. CAAI Transactions on Intelligent Systems, 2020, 15(5): 825834. [3] 刘强, 段富海, 桑勇, 等. 复杂环境下视觉SLAM闭环检测方法综述[J]. 机器人, 2019, 41(1): 112123. LIU Q, DUAN F, SANG Y, et al. A survey of loop-closure detection method of visual SLAM in complex environments[J]. Robot, 2019, 41(1): 112123. [4] 杨淑静, 丛海林, 杨超. 动态运行复杂体系档案信息化管理问题与对策——青岛大学材料学科实训平台[J]. 化学教育(中英文), 2023, 44(4): 115121. YANG S J, CONG H L, YANG C. Problems and countermeasures of archives information management in dynamic operation complex system: material discipline training platform of Qingdao university[J]. Chinese Journal of Chemical of Education, 2023, 44(4):115121. [5] MILFORD M, WYETH G. SeqSLAM: visual route-based navigation for sunny summer days and stormy winter nights[C]//Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). Saint Paul:IEEE, 2012: 16431649. [6] MILFORD M, SHEN C, LOWRY S, et al. Sequence searching with deep-learnt depth for condition and viewpoint invariant route-based place recognition[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). Boston:IEEE, 2015: 1825. [7] TSINTOTAS K, BAMPIS L, RALLIS S, et al. SeqSLAM with bag of visual words for appearance based loop closure detection[C]//Proceedings of the International Conference on Robotics in Alpe-Adria Danube Region. Patras: Springer, 2018: 580587. [8] JEGOU H, DOUZE M, SCHMID C, et al. Aggregating local descriptors into a compact image representation[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR). San Francisco: IEEE, 2010: 33043311. [9] NASEER T, SPINELLO L, BURGARD W, et al. Robust visual robot localization across seasons using network flows[C]//Proceedings of the AAAI Conference on Artificial Intelligence. Quebec: AAAI, 2014: 25642570. [10] HANSEN P, BROWNING B. Visual place recognition using HMM sequence matching[C]//Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems. Chicago: IEEE, 2014: 45494555. [11] SIAM S, ZHANG H. Fast-SeqSLAM: a fast appearance based place recognition algorithm[C]//Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). Singapore: IEEE, 2017: 57025708. [12] MALKOV Y, YASHUNIN D. Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020, 42(4), 824836. [13] KLEINBERG J. Navigation in a small world[J]. Nature, 2000, 406(6798): 845. [14] 周键,董永红.测控实验室内关键节点电压的校正方法仿真[J].计算机仿真,2022,39(7):124127,223. Zhou J, DONG Y H.Simulation of voltage correction method for pilot nodes in measurement and control laboratory[J].Computer Simulation,2022, 39(7):124127,223. [15] ARANDJELOVIC R, GRONAT P, TORII A, et al. NetVLAD: CNN architecture for weakly supervised place recognition[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR). Las Vegas: IEEE, 2016: 52975307.
