grandzxw Goto Github PK
Name: Grandzxw
Type: User
Company: Harbin Institute of Technology
Bio: PhD candidate at HIT. Point Cloud Segmentation, Place Recognition and Multi-robot System
Location: Shenzhen
Name: Grandzxw
Type: User
Company: Harbin Institute of Technology
Bio: PhD candidate at HIT. Point Cloud Segmentation, Place Recognition and Multi-robot System
Location: Shenzhen
Monocular Camera Localization in Prior LiDAR Maps with 2D-3D Line Correspondences
Papers and Datasets about Point Cloud.
3DLines-SLAM: A Monocular Vision Semi-Dense 3D Reconstruction Based on ORB-SLAM Abstract-Producing high-quality 3D maps and calculating more accurate camera pose has always been the goal of SLAM technology. The requirements of SLAM technology such as real-time, low computational cost, and low hardware cost are contradictory to the above objectives. For the issues listed above, we propose a novel semi-dense reconstruction algorithm based on the monocular ORB-SLAM system by matching the line segment features extracted from keyframes. Specifically, we build upon ORB-SLAM, the system first provides a set of keyframes and their corresponding camera poses and a series of map points in real-time. Then we use our developed a keyframe re-culling algorithm to culling redundant keyframes. Then an improved line segment extraction method is used to extract line segments in each keyframe. Finally, we use purely geometric constraints to generates accurate 3D scene model by matching 2D line segments from different keyframes. We thoroughly evaluate and in-depth analysis of our approach, the results show our system runs steadily and reliably. Not only the whole system has strong robustness, but also it can quickly generate an accurate 3d model online with low computational costs.
A simple and efficient 3D line detection algorithm for large scale unorganized point cloud
Advance-LeGO-LOAM
Get the papers you want from ArXiv every day.
A comprehensive list of Implicit Representations and NeRF papers relating to Robotics/RL domain, including papers, codes, and related websites
A comprehensive list of Implicit Representations and NeRF papers relating to SLAM/Robotics domain, including papers, video, codes, and related websites
Drawing Bayesian networks, graphical models, and technical frameworks in LaTeX.
π Awesome LIDAR list. The list includes LIDAR manufacturers, datasets, point cloud-processing algorithms, point cloud frameworks and simulators.
Recent multi-robot projects and papers: Including SLAM, place recognition, Large Language Models navigation. (continually updated)
SLAM algorithms and systems based on Neural Networks.
A list of papers and datasets about point cloud analysis (processing)
A list of papers about point cloud based place recognition, also known as loop closure detection in SLAM (processing)
A curated list of point cloud registration.
A curated list of awesome SLAM tutorials, projects and communities.
A curated list of awesome datasets for SLAM
Dynamic SLAM
Improved YOLO detection by sensor fusion with Mono-VINS on a mobile robot
A tool and examples of general bird-view on KITTI data-set.
ROS packages for Velodyne 3D LIDARs provided by Robo@FIT group.
CAE-LO: LiDAR Odometry Leveraging Fully Unsupervised Convolutional Auto-Encoder for Interest Point Detection and Feature Description
CNN SLAM implementation of https://arxiv.org/abs/1704.03489
ROS package for Robust Optical Flow Using Kernel Cross-Correlators
An implementation of the CPL-Sync algorithm for planar pose graph optimization (PGO)
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π Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. πππ
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google β€οΈ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.