5 papers
Semantic Visual Simultaneous Localization and Mapping: A Survey on State of the Art, Challenges, and Future Directions
Thanh Nguyen Canh, Haolan Zhang, Xiem HoangVan +1
Semantic Simultaneous Localization and Mapping (SLAM) is a critical area of research within robotics and computer vision, focusing on the simultaneous localization of robotic syste…
IL-SLAM: Intelligent Line-assisted SLAM Based on Feature Awareness for Dynamic Environments
Haolan Zhang, Thanh Nguyen Canh, Chenghao Li +3
Visual Simultaneous Localization and Mapping (SLAM) plays a crucial role in autonomous systems. Traditional SLAM methods, based on static environment assumptions, struggle to handl…
SR-SLAM: Scene-reliability Based RGB-D SLAM in Diverse Environments
Haolan Zhang, Chenghao Li, Thanh Nguyen Canh +2
Visual simultaneous localization and mapping (SLAM) plays a critical role in autonomous robotic systems, especially where accurate and reliable measurements are essential for navig…
Adaptive Prior Scene-Object SLAM for Dynamic Environments
Haolan Zhang, Thanh Nguyen Canh, Chenghao Li +1
Visual Simultaneous Localization and Mapping (SLAM) plays a vital role in real-time localization for autonomous systems. However, traditional SLAM methods, which assume a static en…
IRAF-SLAM: An Illumination-Robust and Adaptive Feature-Culling Front-End for Visual SLAM in Challenging Environments
Thanh Nguyen Canh, Bao Nguyen Quoc, Haolan Zhang +3
Robust Visual SLAM (vSLAM) is essential for autonomous systems operating in real-world environments, where challenges such as dynamic objects, low texture, and critically, varying…