RU-SLAM: A Robust Deep-Learning Visual Simultaneous Localization and Mapping (SLAM) System for Weakly Textured Underwater Environments

RU-SLAM: A Robust Deep-Learning Visual Simultaneous Localization and Mapping (SLAM) System for Weakly Textured Underwater Environments

Accurate and robust simultaneous localization and mapping (SLAM) systems are crucial for autonomous underwater vehicles (AUVs) to perform missions in unknown environments. However, directly applying deep learning-based SLAM methods to underwater environments poses challenges due to weak textures, im...

Full description

Bibliographic Details
Main Authors: Zhuo Wang, Qin Cheng, Xiaokai Mu
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Sensors
Subjects:
autonomous underwater vehicle
underwater image
underwater SLAM
deep learning
local and global features
Online Access:https://www.mdpi.com/1424-8220/24/6/1937

Similar Items

Similar Items