ORB-SLAM: a Versatile and Accurate Monocular SLAM System
Reads0
Chats0
TLDR
A survival of the fittest strategy that selects the points and keyframes of the reconstruction leads to excellent robustness and generates a compact and trackable map that only grows if the scene content changes, allowing lifelong operation.Abstract:
This paper presents ORB-SLAM, a feature-based monocular SLAM system that operates in real time, in small and large, indoor and outdoor environments. The system is robust to severe motion clutter, allows wide baseline loop closing and relocalization, and includes full automatic initialization. Building on excellent algorithms of recent years, we designed from scratch a novel system that uses the same features for all SLAM tasks: tracking, mapping, relocalization, and loop closing. A survival of the fittest strategy that selects the points and keyframes of the reconstruction leads to excellent robustness and generates a compact and trackable map that only grows if the scene content changes, allowing lifelong operation. We present an exhaustive evaluation in 27 sequences from the most popular datasets. ORB-SLAM achieves unprecedented performance with respect to other state-of-the-art monocular SLAM approaches. For the benefit of the community, we make the source code public.read more
Citations
More filters
Journal ArticleDOI
GMMLoc: Structure Consistent Visual Localization With Gaussian Mixture Models
TL;DR: In this article, a cross-modality method that tracks a camera in a prior map modelled by the Gaussian Mixture Model (GMM) is presented, with the pose estimated by the front-end initially, and the visual structure from the triangulation is refined simultaneously.
Proceedings ArticleDOI
Adversarial Networks for Camera Pose Regression and Refinement
TL;DR: In this article, the joint distribution of RGB images and their corresponding camera poses using a discriminator network and adversarial learning is learned to optimize the predicted camera poses and thus improve the localization accuracy.
Proceedings ArticleDOI
A mapping of visual SLAM algorithms and their applications in augmented reality
TL;DR: This work investigated the main algorithms of visual SLAM, and its applications in augmented reality, and described the key features of these algorithms and two taxonomies for SLAM techniques are proposed.
Proceedings ArticleDOI
Tightly-Coupled Single-Anchor Ultra-wideband-Aided Monocular Visual Odometry System
TL;DR: This work proposes a tightly-coupled odometry framework, which combines monocular visual feature observations with distance measurements provided by a single ultra-wideband (UWB) anchor with an initial guess for its location to reduce the visual drift and improve the system robustness.
Proceedings ArticleDOI
Accurate Direct Visual-Laser Odometry with Explicit Occlusion Handling and Plane Detection
TL;DR: This paper proposes a direct laser-visual odometry approach building upon photometric image alignment designed to maximize the information usage of both, the image and the laser scan, to compute an accurate frame-to-frame motion estimate.
References
More filters
Journal ArticleDOI
Distinctive Image Features from Scale-Invariant Keypoints
TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
Multiple View Geometry in Computer Vision.
TL;DR: This book is referred to read because it is an inspiring book to give you more chance to get experiences and also thoughts and it will show the best book collections and completed collections.
Book ChapterDOI
SURF: speeded up robust features
TL;DR: A novel scale- and rotation-invariant interest point detector and descriptor, coined SURF (Speeded Up Robust Features), which approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much faster.
Proceedings ArticleDOI
ORB: An efficient alternative to SIFT or SURF
TL;DR: This paper proposes a very fast binary descriptor based on BRIEF, called ORB, which is rotation invariant and resistant to noise, and demonstrates through experiments how ORB is at two orders of magnitude faster than SIFT, while performing as well in many situations.
Journal ArticleDOI
Vision meets robotics: The KITTI dataset
TL;DR: A novel dataset captured from a VW station wagon for use in mobile robotics and autonomous driving research, using a variety of sensor modalities such as high-resolution color and grayscale stereo cameras and a high-precision GPS/IMU inertial navigation system.