4 accepted papers
Visual simultaneous localization and mapping (VSLAM) is a foundational technology in robotics, providing an optimal balance of cost and accuracy. However, existing systems often lack robustness in environments with fast motion, dynamic lighting, or low texture. This letter introduces ML-SLAM, a hybr
Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires agents to navigate 3D environments based on visual observations and natural language instructions. Existing approaches, focused on topological and semantic maps, often face limitations in accurately understanding and adaptin
The semantic segmentation of LiDAR in the outdoor environment is still an open problem in the field of automatic driving. Although the emerging development and technological advancements, it remains challenging for three reasons: 1) uneven distribution of LiDAR Points in 3D space; 2) the same object
Keypoint matching is an important operation in computer vision and its applications such as visual simultaneous localization and mapping (SLAM) in robotics. This matching operation heavily depends on the descriptors of the keypoints, and it must be performed reliably when images undergo conditional…