An overview on visual slam: From tradition to semantic
W Chen, G Shang, A Ji, C Zhou, X Wang, C Xu, Z Li… - Remote Sensing, 2022 - mdpi.com
Visual SLAM (VSLAM) has been developing rapidly due to its advantages of low-cost
sensors, the easy fusion of other sensors, and richer environmental information. Traditional …
sensors, the easy fusion of other sensors, and richer environmental information. Traditional …
Deep learning sensor fusion for autonomous vehicle perception and localization: A review
Autonomous vehicles (AV) are expected to improve, reshape, and revolutionize the future of
ground transportation. It is anticipated that ordinary vehicles will one day be replaced with …
ground transportation. It is anticipated that ordinary vehicles will one day be replaced with …
Robust dynamic radiance fields
Dynamic radiance field reconstruction methods aim to model the time-varying structure and
appearance of a dynamic scene. Existing methods, however, assume that accurate camera …
appearance of a dynamic scene. Existing methods, however, assume that accurate camera …
Point-slam: Dense neural point cloud-based slam
We propose a dense neural simultaneous localization and mapping (SLAM) approach for
monocular RGBD input which anchors the features of a neural scene representation in a …
monocular RGBD input which anchors the features of a neural scene representation in a …
Suma++: Efficient lidar-based semantic slam
Reliable and accurate localization and mapping are key components of most autonomous
systems. Besides geometric information about the mapped environment, the semantics …
systems. Besides geometric information about the mapped environment, the semantics …
RDS-SLAM: Real-time dynamic SLAM using semantic segmentation methods
The scene rigidity is a strong assumption in typical visual Simultaneous Localization and
Mapping (vSLAM) algorithms. Such strong assumption limits the usage of most vSLAM in …
Mapping (vSLAM) algorithms. Such strong assumption limits the usage of most vSLAM in …
YOLO-SLAM: A semantic SLAM system towards dynamic environment with geometric constraint
Simultaneous localization and mapping (SLAM), as one of the core prerequisite
technologies for intelligent mobile robots, has attracted much attention in recent years …
technologies for intelligent mobile robots, has attracted much attention in recent years …
Dynamic-SLAM: Semantic monocular visual localization and mapping based on deep learning in dynamic environment
When working in dynamic environment, traditional SLAM framework performs poorly due to
interference from dynamic objects. By taking advantages of deep learning in object …
interference from dynamic objects. By taking advantages of deep learning in object …
Blitz-SLAM: A semantic SLAM in dynamic environments
Y Fan, Q Zhang, Y Tang, S Liu, H Han - Pattern Recognition, 2022 - Elsevier
Static environment is a prerequisite for most of visual simultaneous localization and
mapping systems. Such a strong assumption limits the practical application of most existing …
mapping systems. Such a strong assumption limits the practical application of most existing …
Visual slam: What are the current trends and what to expect?
In recent years, Simultaneous Localization and Mapping (SLAM) systems have shown
significant performance, accuracy, and efficiency gain. In this regard, Visual Simultaneous …
significant performance, accuracy, and efficiency gain. In this regard, Visual Simultaneous …