© 2018 IEEE. This paper presents an experimental evaluation of monocular ORB-SLAM applied to underwater scenarios. It is investigated as an alternative SLAM method with minimal instu-mentation compared to other approaches that integrate different sensors such as inertial and acoustic sensors. ORB-SLAM creates a 3D map based on image frames and estimates the position of the robot by using a feature-based front-end and a graph-based back-end. The performance of ORB-SLAM is evaluated through experiments in different settings with varying lighting, visibility and water dynamics. Results show good performance given the right conditions and demonstrate that ORB-SLAM can work well in the underwater environment. Based on our findings the paper outlines possible enhancements which should further improve on the algorithms performance.
|Idioma original||Inglés estadounidense|
|Estado||Publicada - 4 dic 2018|
|Publicado de forma externa||Sí|
|Evento||2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018 - |
Duración: 4 dic 2018 → …
|Conferencia||2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018|
|Período||4/12/18 → …|