Deep Visual Odometry Methods for Mobile Robots
It addresses navigation challenges for mobile robots in human environments, but appears incremental as it builds on existing visual odometry techniques.
This paper tackles the problem of navigation for mobile robots by exploring deep visual odometry methods, which enable real-time 3D navigation and solve challenges like Simultaneous Localization and Mapping (SLAM) and 3D map reconstruction, though no concrete results or numbers are provided.
Technology has made navigation in 3D real time possible and this has made possible what seemed impossible. This paper explores the aspect of deep visual odometry methods for mobile robots. Visual odometry has been instrumental in making this navigation successful. Noticeable challenges in mobile robots including the inability to attain Simultaneous Localization and Mapping have been solved by visual odometry through its cameras which are suitable for human environments. More intuitive, precise and accurate detection have been made possible by visual odometry in mobile robots. Another challenge in the mobile robot world is the 3D map reconstruction for exploration. A dense map in mobile robots can facilitate for localization and more accurate findings.