Journal of Guangdong University of Technology ›› 2021, Vol. 38 ›› Issue (04): 65-70.doi: 10.12052/gdutxb.200138

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Direct Sparse Visual Odometer Based on Enhanced Stereo-Camera Constraints

Ye Pei-chu, Li Dong, Zhang Yun   

  1. School of Automation, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2020-10-16 Online:2021-07-10 Published:2021-05-25

Abstract: A new direct SLAM (Simultaneous Localization And Mapping) system with enhanced stereo-camera constrains based on Stereo Direct Sparse Odometry (Stereo DSO) is presented. As a direct SLAM method, any image pixel with sufficient intensity gradient can be utilized, which makes it robust even in featureless areas. Two-stage checking combining SAD (Sum of Absolute Differences) with NCC (Normalized Cross Correlation) matching method is used for stereo matching and triangulated uncertainty concerned to accelerate the convergence of depth filters. To estimate the accurate scale of the environment, static stereo constrains are added to the tracking module. Our evaluation on KITTI demonstrates that the proposed system achieves the better performance than the state of the art direct SLAM systems such as LSD-SLAM2 and Stereo DSO, and achieves the comparable performance with ORB-SLAM3 which is the state of the art feature SLAM. The proposal provides mobile robots with a new direct SLAM system to explore the environment more precisely and robustly.

Key words: visual odometer, direct method, mobile robot, simultaneous localization and mapping(SLAM)

CLC Number: 

  • TP391.4
[1] CADNA 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): 1309-1332.
[2] FUENTES-PACHECO J, RUIZ-ASCENCIO J, RENDON-MANCHA J M. Visual simultaneous localization and mapping: a survey [J]. Artificial Intelligence Review, 2015, 43(1): 55-81.
[3] 朱福利, 曾碧, 曹军. 基于粒子滤波的 SLAM 算法并行优化与实现[J]. 广东工业大学学报, 2017, 34(2): 92-96.
ZHU F L, ZENG B, CAO J. Parallel optimization and implementation of SLAM algorithm based on particle filter [J]. Journal of Guangdong University of Technology, 2017, 34(2): 92-96.
[4] WEI W, TAN L, JIN G, et al. A survey of UAV visual navigation based on monocular SLAM[C]//2018 IEEE 4th Information Technology and Mechatronics Engineering Conference (ITOEC). Chongqing: IEEE, 2018: 1849-1853.
[5] ROS G, SAPPA A, PONSA D, et al. Visual slam for driverless cars: a brief survey[C]//Intelligent Vehicles Symposium (IV) Workshops. Alcala de Henares: IEEE, 2012, 2.
[6] LIANG M J, MIN H Q, LUO R. Graph-based SLAM: a survey [J]. Robot, 2013, 35(4): 500-512.
[7] KLEIN G, MURRAY D. Parallel tracking and mapping for small AR workspaces[C]//2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality. Nara: IEEE, 2007: 225-234.
[8] MUR-ARTAL R, MONTIEL J M M, TARDOS J D. ORB-SLAM: a versatile and accurate monocular SLAM system [J]. IEEE Transactions on Robotics, 2015, 31(5): 1147-1163.
[9] MUR-ARTAL R, TARDOS J D. ORB-SLAM2: an open-source slam system for monocular, stereo, and RGB-D cameras [J]. IEEE Transactions on Robotics, 2017, 33(5): 1255-1262.
[10] CAMPOS C, ELVIRA R, RODRIGUEZ J J G, et al. ORB-SLAM3: an accurate open-source library for visual, visual-inertial and multi-map SLAM[J]. arXiv: 2007. 11898.
[11] KERL C, STURM J, CREMERS D. Dense visual SLAM for RGB-D cameras[C]//2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. Tokyo: IEEE, 2013: 2100-2106.
[12] ENGEL J, SCHOPS T, CREMERS D. LSD-SLAM: large-scale direct monocular SLAM[C]//European Conference On Computer Vision. Zurich: Springer, 2014: 834-849.
[13] ENGEL J, KOLTUN V, CREMERS D. Direct sparse odometry [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, 40(3): 611-625.
[14] WANG R, SCHWORER M, CREMERS D. Stereo DSO: large-scale direct sparse visual odometry with stereo cameras[C]//Proceedings of the IEEE International Conference on Computer Vision. Venice: IEEE, 2017: 3903-3911.
[15] HEO Y S, LEE K M, LEE S U. Robust stereo matching using adaptive normalized cross-correlation [J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2010, 33(4): 807-822.
[16] CVISIC I, CESIC J, MARKOVIC I, et al. SOFT-SLAM: computationally efficient stereo visual simultaneous localization and mapping for autonomous unmanned aerial vehicles [J]. Journal of Field Robotics, 2018, 35(4): 578-595.
[17] VANNE J, AHO E, HAMALAINEN T D, et al. A high-performance sum of absolute difference implementation for motion estimation [J]. IEEE Transactions on Circuits and Systems for Video Technology, 2006, 16(7): 876-883.
[18] FORSTER C, PIZZOLI M, DAVIDE S. SVO: fast semi-direct monocular visual odometry[C]//IEEE International Conference on Robotics & Automation. Hong Kong: IEEE, 2014.
[19] ZHANG Z, DONG P, WANG J, et al. Improving S-MSCKF with variational bayesian adaptive nonlinear filter [J]. IEEE Sensors Journal, 2020, 20(16): 9437-9448.
[20] GEIGER A, LENZ P, STILLER C, et al. Vision meets robotics: the kitti dataset [J]. The International Journal of Robotics Research, 2013, 32(11): 1231-1237.
[21] ENGEL J, STUCKLER J, CREMERS D. Large-scale direct SLAM with stereo cameras[C]//2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Hamburg: IEEE, 2015: 1935-1942.
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