Simultaneous localization and map** (slam) for autonomous driving: concept and analysis
S Zheng, J Wang, C Rizos, W Ding, A El-Mowafy - Remote Sensing, 2023 - mdpi.com
The Simultaneous Localization and Map** (SLAM) technique has achieved astonishing
progress over the last few decades and has generated considerable interest in the …
progress over the last few decades and has generated considerable interest in the …
Translo: A window-based masked point transformer framework for large-scale lidar odometry
Recently, transformer architecture has gained great success in the computer vision
community, such as image classification, object detection, etc. Nonetheless, its application …
community, such as image classification, object detection, etc. Nonetheless, its application …
Dvlo: Deep visual-lidar odometry with local-to-global feature fusion and bi-directional structure alignment
Abstract Information inside visual and LiDAR data is well complementary derived from the
fine-grained texture of images and massive geometric information in point clouds. However …
fine-grained texture of images and massive geometric information in point clouds. However …
4DRVO-Net: Deep 4D radar–visual odometry using multi-modal and multi-scale adaptive fusion
Four-dimensional (4D) radar–visual odometry (4DRVO) integrates complementary
information from 4D radar and cameras, making it an attractive solution for achieving …
information from 4D radar and cameras, making it an attractive solution for achieving …
HypLiLoc: Towards effective LiDAR pose regression with hyperbolic fusion
LiDAR relocalization plays a crucial role in many fields, including robotics, autonomous
driving, and computer vision. LiDAR-based retrieval from a database typically incurs high …
driving, and computer vision. LiDAR-based retrieval from a database typically incurs high …
Self-supervised monocular depth estimation with self-perceptual anomaly handling
It is attractive to extract plausible 3-D information from a single 2-D image, and self-
supervised learning has shown impressive potential in this field. However, when only …
supervised learning has shown impressive potential in this field. However, when only …
LiDAR-based localization using universal encoding and memory-aware regression
Visual localization is critical to many robotics and computer vision applications. Absolute
pose regression performs localization by encoding scene features followed by pose …
pose regression performs localization by encoding scene features followed by pose …
Moda: Map style transfer for self-supervised domain adaptation of embodied agents
We propose a domain adaptation method, MoDA, which adapts a pretrained embodied
agent to a new, noisy environment without ground-truth supervision. Map-based memory …
agent to a new, noisy environment without ground-truth supervision. Map-based memory …
Self-supervised ego-motion estimation based on multi-layer fusion of rgb and inferred depth
Z Jiang, H Taira, N Miyashita… - … Conference on Robotics …, 2022 - ieeexplore.ieee.org
In existing self-supervised depth and ego-motion estimation methods, ego-motion estimation
is usually limited to only leveraging RGB information. Recently, several methods have been …
is usually limited to only leveraging RGB information. Recently, several methods have been …
Calibrating Panoramic Depth Estimation for Practical Localization and Map**
The absolute depth values of surrounding environments provide crucial cues for various
assistive technologies, such as localization, navigation, and 3D structure estimation. We …
assistive technologies, such as localization, navigation, and 3D structure estimation. We …