NaveGo: an open-source MATLAB/GNU Octave toolbox for processing integrated navigation systems and performing inertial sensors analysis.

This is a package for extrinsic calibration between a 3D LiDAR and a camera, described in paper: Improvements to Target-Based 3D LiDAR to Camera Calibration. This package is used for Cassie Blue's 3D LiDAR semantic mapping and automation.

LiDAR-Inertial 3D Plane Simulator

A Laser-Camera Calibration Toolbox extending from that at http://www.cs.cmu.edu/~ranjith/lcct.html

Visualization of vehicle position and pose estimation in Google Earth

interfaces and algorithms for event based cameras, lidars, and actuators

Probabilistic line extraction from 2-D range scan

A collection of digital forestry tools for Matlab/Octave

MATLAB code for LiDAR-Camera-GNSS/INS extrinsic calibration based on hand-eye calibration method.

Given a map data (image + lidar), estimate the 6 DoF camera pose of the query image.

Object detection and transfer learning on point clouds using pretrained Complex-YOLOv4 models in MATLAB

LiDAR data processing, object recognition from point clouds, and LiDAR remote sensing.

NRT lidar data processing program for multiwavelength polarization Raman lidar network (PollyNET)

Code and documents to support the Thesis: Progress Towards LiDAR Based Bicycle Detection in Urban Environments Edit Add topics

Semantic segmentation and transfer learning using pretrained SalsaNext model in MATLAB

polarPcolor draws a pseudocolor plot in polar coordinates with a polar grid.

Calculation volume of terrain object by point cloud

This package introduces the concept of optimizing target shape to remove pose ambiguity for LiDAR point clouds. Both the simulation and the experimental results confirm that by using the optimal shape and the global solver, we achieve centimeter error in translation and a few degrees in rotation even when a partially illuminated target is placed…

Prototype implementation of a non-rigid point cloud registration algorithm using piece-wise tricubic polynomials as transformation model.

Data fusion methods that improve the localization estimates of two communicating vehicles equipped with a LIDAR