Hybrid Visual Odometry Algorithm Using a Downward-Facing Monocular Camera

Author:

Al-Hadithi Basil Mohammed12ORCID,Thomas David3ORCID,Pastor Carlos1

Affiliation:

1. Intelligent Control Group, Centre for Automation and Robotics UPM-CSIC, Universidad Politécnica de Madrid, C/J, Gutiérrez Abascal, 2, 28006 Madrid, Spain

2. Department of Electrical, Electronics, Control Engineering and Applied Physics, School of Industrial Design and Engineering, Universidad Politécnica de Madrid, C/Ronda de Valencia, 3, 28012 Madrid, Spain

3. School of Industrial Engineering, Universidad Politécnica de Madrid, C/J, Gutiérrez Abascal, 2, 28006 Madrid, Spain

Abstract

The increasing interest in developing robots capable of navigating autonomously has led to the necessity of developing robust methods that enable these robots to operate in challenging and dynamic environments. Visual odometry (VO) has emerged in this context as a key technique, offering the possibility of estimating the position of a robot using sequences of onboard cameras. In this paper, a VO algorithm is proposed that achieves sub-pixel precision by combining optical flow and direct methods. This approach uses only a downward-facing, monocular camera, eliminating the need for additional sensors. The experimental results demonstrate the robustness of the developed method across various surfaces, achieving minimal drift errors in calculation.

Publisher

MDPI AG

Reference24 articles.

1. Song, X., Althoefer, K., and Seneviratne, L. (2010, January 7–10). A robust downward-looking camera based velocity estimation with height compensation for mobile robots. Proceedings of the 2010 11th International Conference on Control Automation Robotics & Vision, Singapore.

2. Optical Flow-Based Stereo Visual Odometry with Dynamic Object Detection;Liu;IEEE Trans. Comput. Soc. Syst.,2022

3. Soft2: Stereo visual odometry for road vehicles based on a point-to-epipolar-line metric;IEEE Trans. Robot.,2022

4. Stereo visual odometry with automatic brightness adjustment and feature tracking prediction;Yin;IEEE Trans. Instrum. Meas.,2022

5. Mutual information based feature selection for stereo visual odometry;Kottath;J. Intell. Robot. Syst.,2020

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