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A Binocular MSCKF-Based Visual Inertial Odometry System Using LK Optical Flow

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Abstract

The odometry is an important part of intelligent mobile robots to achieve positioning and navigation functions. At present, the mainstream visual odometry locates only through the visual information obtained by camera sensors. Therefore, in the case of insufficient light, texture missing and camera jitter, the visual odometry is difficult to locate accurately. To solve the problem, we propose a binocular MSCKF-based visual inertial odometry system using Lucas-Kanade (LK) optical flow. Firstly, the Inertial Measurement Unit (IMU) is introduced to overcome the above problems. Moreover, LK optical flow algorithm is utilized to process the visual information obtained by the binocular camera, and MSCKF algorithm is employed to realize the fusion of visual information and inertial information, which improves the accuracy and efficiency of the visual inertial odometry system positioning. Finally, the proposed method is simulated on the European Robotics Challenge (EuRoc) dataset by Robot Operating System (ROS), and compared with two other advanced visual inertial odometry systems, ROVIO and MSCKF-mono. A large number of simulations verify that the proposed method can achieve accurate pose estimation, which is superior to the two existing advanced visual inertial odometry systems.

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Acknowledgements

The work is supported by the National Natural Science Foundation of China (No.61873176). Natural Science Foundation of Jiangsu Province, China (BK20181433); The open fund for the Jiangsu Smart Factory Engineering Research Center; Postgraduate Research & Practice Innovation Program of Jiangsu Province(KYCX19_1927).The authors would like to thank the referees for their constructive comments.

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Authors and Affiliations

  1. School of Mechanical and Electric Engineering, Soochow University, Suzhou, China

    Guangqiang Li & Lei Yu

  2. Jiangsu Smart Factory Engineering Research Center, Huaiyin institute of technology, Huai’an, China

    Lei Yu

  3. School of Automation, Southeast University, Nanjing, China

    Shumin Fei

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  1. Guangqiang Li
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  2. Lei Yu
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Correspondence to Lei Yu.

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Li, G., Yu, L. & Fei, S. A Binocular MSCKF-Based Visual Inertial Odometry System Using LK Optical Flow. J Intell Robot Syst 100, 1179–1194 (2020). https://doi.org/10.1007/s10846-020-01222-z

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