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Research on GDR Obstacle Detection Method Based on Stereo Vision

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Abstract

In this paper, we propose a method of obstacle detection for guide dog robots based on stereo vision. Theoretically, we analyze the lens imaging principle of a binocular camera and 3D ranging method and calibrate the checkerboard grid images of different angles based on MATLAB. Through the study and analysis of the stereo-matching algorithm, we obtain accurate depth information. Using the contour extraction algorithm to solve the contour of the obstacle and the area of the convex package; then set the area threshold to filter out the false detection part, to quickly and effectively calculate the position coordinates of the obstacle, and finally obtain the 3D stereo information of the environment ahead. The algorithm proposed in this paper is verified on the experimental platform built. The experimental results show that the algorithm is effective and feasible.

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Funding

This work was supported by ongoing institutional funding. No additional grants to carry out or direct this particular research were obtained.

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All authors contributed to the study’s conception and design. Experiment preparation, data collection, and analysis were performed by Jing Hou, Zhangxi Lin, Meimei Chen, and Yihang Guo. The first draft of the manuscript was written by Bin Hong and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Bin Hong.

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Jing Hou, Chen, M., Guo, Y. et al. Research on GDR Obstacle Detection Method Based on Stereo Vision. Aut. Control Comp. Sci. 58, 90–100 (2024). https://doi.org/10.3103/S0146411624010061

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  • DOI: https://doi.org/10.3103/S0146411624010061

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