Deep Learning Techniques for Visual SLAM: A Survey
Visual Simultaneous Localization and Mapping (VSLAM) has attracted considerable attention in recent years. This task involves using visual sensors to localize a robot while simultaneously constructing an internal representation of its environment. Traditional VSLAM methods involve the laborious hand...
Main Authors: | Saad Mokssit, Daniel Bonilla Licea, Bassma Guermah, Mounir Ghogho |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10054007/ |
Similar Items
-
Deep Learning for Visual SLAM: The State-of-the-Art and Future Trends
by: Margarita N. Favorskaya
Published: (2023-04-01) -
An Intelligent Navigation Control Approach for Autonomous Unmanned Vehicles via Deep Learning-Enhanced Visual SLAM Framework
by: Lu Chen, et al.
Published: (2023-01-01) -
Multi-Objective Location and Mapping Based on Deep Learning and Visual Slam
by: Ying Sun, et al.
Published: (2022-10-01) -
Spatio-Temporal Forecasting: A Survey of Data-Driven Models Using Exogenous Data
by: Safaa Berkani, et al.
Published: (2023-01-01) -
A Comprehensive Survey of Visual SLAM Algorithms
by: Andréa Macario Barros, et al.
Published: (2022-02-01)