A Comparison Study on Replacing Stereo Disparity with LiDAR in Visual Odometry Methods

Autor: Petrut Cobarzan, Sergiu Nedevschi, Catalin Golban
Rok vydání: 2020
Předmět:
Zdroj: ICCP
DOI: 10.1109/iccp51029.2020.9266228
Popis: The visual-based odometry estimation is a key feature in today’s autonomous robots. Although the best performance for video-only solutions is achieved with stereo cameras, the LiDAR sensors’ general suitability for precise depth measurements at reasonable density, leads to the idea of fusing monocular cameras with LiDAR depth maps for the task of visual odometry. This paper presents a method for replacing depths computed using disparity estimation techniques with LiDAR based depth estimation, in the frame-to-frame stereo visual odometry method described in [2]. A comparative evaluation of the performance obtained by the same framework method using one or the other depth measurement source is presented in detail, concluding that the LiDAR measurements are suitable as input in existing visual odometry techniques, leading to increased estimation precision.
Databáze: OpenAIRE