Enhancing robustness and efficiency in visual SLAM through integration of deep learning-based semantic segmentation techniques
Visual SLAM is a robotics system enabling the traversal of robots in new environments without prior information. With the camera as its main sensor, it achieves the aforementioned objective through localisation and mapping algorithms based on visual information. To counter the vulnerability of...
Saved in:
Main Author: | Halim, Jessica |
---|---|
Other Authors: | Loke Yuan Ren |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/175555 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Fast semantic-aware motion state detection for visual SLAM in dynamic environment
by: Singh, Gaurav, et al.
Published: (2024) -
CoSLAM: Collaborative visual SLAM in dynamic environments
by: Zou, D., et al.
Published: (2014) -
Integrated and scalable augmented reality multiplayer robotic platform
by: Tandianus, Budianto, et al.
Published: (2020) -
Appearance-based SLAM with map loop closing using an omnidirectional camera
by: Saedan, M., et al.
Published: (2014) -
Implementing LiDAR-based SLAM algorithms for enhanced mapping and localization in physical robots
by: Ang, Ken Huat
Published: (2024)