A novel deep learning solution for the automatic roofing material classification of the Dutch building stock using aerial imagery and laser scanning data fusion.
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Updated
Jun 11, 2024 - Jupyter Notebook
A novel deep learning solution for the automatic roofing material classification of the Dutch building stock using aerial imagery and laser scanning data fusion.
The Aarohan Project focuses on developing an advanced autonomous rover for Moon exploration. This project involves autonomous navigation using LiDAR and camera sensors, robust mobility systems, RF communication, and a 6-degree-of-freedom robotic arm for object. It aims to enhance obstacle avoidance, mobility, and task efficiency in complex terrains
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This is a read-only mirror of https://gitlab.com/pytools4dart/pytools4dart.
A feature line extractor from terrain point cloud data using projection-based approach.
A Deep Learning Classification Framework with Spectral and Spatial Feature Fusion Layers for Hyperspectral and Lidar Sensor Data
[IEEE ICRA'23] A new lightweight LiDAR-inertial odometry algorithm with a novel coarse-to-fine approach in constructing continuous-time trajectories for precise motion correction.
Open source solution for inspecting and generating 3D Tiles for urban environments
Awesome 2D LiDAR list - specs, protocols, wiring, code, identification photos/videos, performance evaluations
Tutorial for creating DSM from LiDAR data in R
A fully templated C++ implementation of general-use algorithms for robotic perception and visual servoing.
Visualization, processing and analysis of Lidar point clouds, mainly focused on forest environment. New version of 3D Forest. Process files with terabytes of data. Edit new point attributes. Simple addition of new features by plugins.
LSD (LiDAR SLAM & Detection) is an open source perception architecture for autonomous vehicle/robotic
LiDAR processing ROS2. Segmentation algorithm: "Fast Ground Segmentation for 3D LiDAR Point Cloud Based on Jump-Convolution-Process". Clustering algorithm: "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance".
Asensing product and development documentation
This is a fiducial marker system designed for LiDAR sensors. Different visual fiducial marker systems (Apriltag, ArUco, CCTag, etc.) can be easily embedded. The usage is as convenient as that of the visual fiducial marker. The system shows potential in SLAM, multi-sensor calibration, augmented reality, and so on.
Automatic Lidar and Ceilometer Processing Framework (ALCF)
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