Courses & Tutorials

Awesome LIDAR – Massive Collection of Resources

A curated list of awesome LIDAR sensors and its applications.

LIDAR is a remote sensing sensor that uses laser light to measure the surroundings in ~cm accuracy. The sensory data is usually referred as point cloud which means set of data points in 3D or 2D. The list contains hardwares, datasets, point cloud-processing algorithms, point cloud frameworks, simulators etc.

Contents

Conventions

  • Any list item with an OctoCat :octocat: has a GitHub repo or organization
  • Any list item with a RedCircle 🔴 has YouTube videos or channel
  • Any list item with a Paper 📰 has a scientific paper or detailed description

Manufacturers

Datasets

  • Ford Dataset – The dataset is time-stamped and contains raw data from all the sensors, calibration values, pose trajectory, ground truth pose, and 3D maps. The data is Robot Operating System (ROS) compatible.
  • Audi A2D2 Dataset – The dataset features 2D semantic segmentation, 3D point clouds, 3D bounding boxes, and vehicle bus data.
  • Waymo Open Dataset – The dataset contains independently-generated labels for lidar and camera data, not simply projections.
  • Oxford RobotCar – The Oxford RobotCar Dataset contains over 100 repetitions of a consistent route through Oxford, UK, captured over a period of over a year.
  • EU Long-term Dataset – This dataset was collected with our robocar (in human driving mode of course), equipped up to eleven heterogeneous sensors, in the downtown (for long-term data) and a suburb (for roundabout data) of Montbéliard in France. The vehicle speed was limited to 50 km/h following the French traffic rules.
  • NuScenes – Public large-scale dataset for autonomous driving.
  • Lyft – Public dataset collected by a fleet of Ford Fusion vehicles equipped with LIDAR and camera.
  • KITTI – Widespread public dataset, pirmarily focusing on computer vision applications, but also contains LIDAR point cloud.
  • Semantic KITTI – Dataset for semantic and panoptic scene segmentation.
  • CADC – Canadian Adverse Driving Conditions Dataset – Public large-scale dataset for autonomous driving in adverse weather conditions (snowy weather).
  • UofTPed50 Dataset – University of Toronto, aUToronto’s self-driving car dataset, which contains GPS/IMU, 3D LIDAR, and Monocular camera data. It can be used for 3D pedestrian detection.
  • PandaSet Open Dataset – Public large-scale dataset for autonomous driving provided by Hesai & Scale. It enables researchers to study challenging urban driving situations using the full sensor suit of a real self-driving-car.
  • Cirrus dataset A public datatset from non-uniform distribution of LIDAR scanning patterns with emphasis on long range. In this dataset Luminar Hydra LIDAR is used. The dataset is available at the Volvo Cars Innovation Portal.

Libraries

Frameworks

Algorithms

Basic matching algorithms

Semantic segmentation

Simultaneous localization and mapping SLAM and LIDAR-based odometry and or mapping LOAM

Object detection and object tracking

Simulators

Others

  • Pointcloudprinter :octocat: – A tool to turn point cloud data from aerial lidar scans into solid meshes for 3D printing.
  • Pcx :octocat: – Point cloud importer/renderer for Unity.
  • Bpy :octocat: – Point cloud importer/renderer/editor for Blender, Point Cloud visualizer.
  • Semantic Segmentation Editor :octocat: – Point cloud and image semantic segmentation editor by Hitachi Automotive And Industry Laboratory.
  • Photogrammetry importer :octocat: – Blender addon to import reconstruction results of several libraries.

Related Articles

Leave a Reply

Your email address will not be published. Required fields are marked *

Back to top button