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GLIO: Tightly-Coupled GNSS/LiDAR/IMU Integration for Continuous and Drift-free State Estimation
Just for our dataset validation, we appreciate and respect the authors' efforts for their contribution to the research community. Reminder: Since the latest version of orbslam3 opencv conflicts wit…
this is very basic version for our dataset validation, only change the path, and align the frame of vio and Groundtruth
An Open-source Package for GNSS Positioning and Real-time Kinematic Using Factor Graph Optimization
Eclipse SUMO is an open source, highly portable, microscopic and continuous traffic simulation package designed to handle large networks. It allows for intermodal simulation including pedestrians a…
PcapPlusPlus is a multiplatform C++ library for capturing, parsing and crafting of network packets. It is designed to be efficient, powerful and easy to use. It provides C++ wrappers for the most p…
Monitoring the code for navigation purpose
A curated list of awesome header-only C++ libraries
Landing page for Shonan Averaging algorithm, a computer vision technique used in 3D reconstruction and mapping.
Extremely simple yet powerful header-only C++ plotting library built on the popular matplotlib
Predict dense depth maps from sparse and noisy LiDAR frames guided by RGB images. (Ranked 1st place on KITTI) [MVA 2019]
Create a rosbag from a given one, using a simple GUI
Finding sufficient initial guesses for offline SLAM.
Python implementation of a bunch of multi-robot path-planning algorithms.
interactive visualization of 5 popular gradient descent methods with step-by-step illustration and hyperparameter tuning UI
UrbanLoco: A Full Sensor Suite Dataset for Mapping and Localization in Urban Scenes
UrbanNav: an Open-Sourcing Localization Data Collected in Asian Urban Canyons, Including Tokyo and Hong Kong
IMU-Lidar Extrinsic Calibration Package
Algorithm to find peaks in a std::vector<float>
Ground Segmentation from Lidar Point Clouds
A ROS package tool to analyze the IMU performance.
A CUDA implementation of SIFT for NVidia GPUs (1.2 ms on a GTX 1060)