Visual-inertial odometry based on exposure controlled by gradient information

被引：1
|
作者：
Lu K. [1 ]
Wang C. [1 ]
Wu J. [1 ]
Qian F. [1 ]
机构：
[1] Aviation Operations and Service Institute, Naval Aviation University, Yantai
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2023年 / 45卷 / 05期
关键词：
direct method; exposure time; inertial measurement unit (IMU); odometry;
D O I：
10.12305/j.issn.1001-506X.2023.05.26
中图分类号：
学科分类号：
摘要：
In visual-inertial odometry (VIO), the direct method is based on the assumption of invariance of brightness, which limits the performance in scenes with rapid brightness changes, and different exposure time will lead to difference in the brightness values of the same object. To solve this problem, an active exposure control algorithm for VIO is proposed, which dynamically adjusts the exposure time of the camera according to the image gradient information to maximize the available information and improve the visual feature extraction and tracking stability. The algorithm is applied to VIO for experimental verification, and the results show that the improved VIO has improved localization performance. © 2023 Chinese Institute of Electronics. All rights reserved.
引用
收藏
页码：1496 / 1502
页数：6
相关论文
共 30 条
  • [1] FORSTER C, PIZZOLI M, SCARAMUZZA D., SVO: fast semi-direct monocular visual odometry, Proc. of the IEEE International Conference on Robotics and Automation, pp. 15-22, (2014)
  • [2] ENGEL J, SCHOPS T, CREMERS D., LSD-SLAM: large-scale direct monocular SLAM, Proc. of the European Conference on Computer Vision, pp. 834-849, (2014)
  • [3] USENKO V, ENGEL J, STUCKLER J, Et al., Direct visual-inertial odometry with stereo cameras, Proc. of the IEEE International Conference on Robotics and Automation, pp. 1885-1892, (2016)
  • [4] YANG Z F, SHEN S J., Monocular visual-inertial state estimation with online initialization and camera-IMU extrinsic calibration, IEEE Trans.on Automation Science and Engineering, 14, 1, pp. 39-51, (2016)
  • [5] LEUTENEGGER S, LYNEN S, BOSSE M, Et al., Keyframe-based visual-inertial odometry using nonlinear optimization, The International Journal of Robotics Research, 34, 3, pp. 314-334, (2015)
  • [6] LI M, MOURIKIS A I., High-precision, consistent EKF-based visual-inertial odometry, The International Journal of Robot-tics Research, 32, 6, pp. 690-711, (2013)
  • [7] NEWCOMBE R A, LOVEGROVE S J, DAVISON A J., DTAM: dense tracking and mapping in real-time, Proc. of the International Conference on Computer Vision, pp. 2320-2327, (2011)
  • [8] KERL C, STURM J, CREMERS D., Dense visual SLAM for RGB-D cameras, Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2100-2106, (2013)
  • [9] PIZZOLI M, FORSTER C, SCARAMUZZA D., REMODE: probabilistic, monocular dense reconstruction in real time, Proc. of the IEEE International Conference on Robotics and Automation, pp. 2609-2616, (2014)
  • [10] ENGEL J, USENKO V, CREMERS D., A photometrically calibrated benchmark for monocular visual odometry
123