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 …

Deep learning sensor fusion for autonomous vehicle perception and localization: A review

J Fayyad, MA Jaradat, D Gruyer, H Najjaran - Sensors, 2020 - mdpi.com
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 …

Robust dynamic radiance fields

YL Liu, C Gao, A Meuleman… - Proceedings of the …, 2023 - openaccess.thecvf.com
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 …

Point-slam: Dense neural point cloud-based slam

E Sandström, Y Li, L Van Gool… - Proceedings of the …, 2023 - openaccess.thecvf.com
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 …

Suma++: Efficient lidar-based semantic slam

X Chen, A Milioto, E Palazzolo… - 2019 IEEE/RSJ …, 2019 - ieeexplore.ieee.org
Reliable and accurate localization and mapping are key components of most autonomous
systems. Besides geometric information about the mapped environment, the semantics …

RDS-SLAM: Real-time dynamic SLAM using semantic segmentation methods

Y Liu, J Miura - Ieee Access, 2021 - ieeexplore.ieee.org
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 …

YOLO-SLAM: A semantic SLAM system towards dynamic environment with geometric constraint

W Wu, L Guo, H Gao, Z You, Y Liu, Z Chen - Neural Computing and …, 2022 - Springer
Simultaneous localization and mapping (SLAM), as one of the core prerequisite
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

L Xiao, J Wang, X Qiu, Z Rong, X Zou - Robotics and Autonomous Systems, 2019 - Elsevier
When working in dynamic environment, traditional SLAM framework performs poorly due to
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 …

Visual slam: What are the current trends and what to expect?

A Tourani, H Bavle, JL Sanchez-Lopez, H Voos - Sensors, 2022 - mdpi.com
In recent years, Simultaneous Localization and Mapping (SLAM) systems have shown
significant performance, accuracy, and efficiency gain. In this regard, Visual Simultaneous …