/awesome-lidar

😎 Awesome LIDAR list. The list includes LIDAR manufacturers, datasets, point cloud-processing algorithms, point cloud frameworks and simulators.

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Awesome LIDAR Awesome

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.

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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.
  • USyd Dataset- The Univerisity of Sydney Campus- Dataset - Long-term, large-scale dataset collected over the period of 1.5 years on a weekly basis over the University of Sydney campus and surrounds. It includes multiple sensor modalities and covers various environmental conditions. ROS compatible
  • Brno Urban Dataset :octocat: - Navigation and localisation dataset for self driving cars and autonomous robots in Brno, Czechia.
  • Argoverse :octocat: - A dataset designed to support autonomous vehicle perception tasks including 3D tracking and motion forecasting collected in Pittsburgh, Pennsylvania and Miami, Florida, USA.
  • Boreas Dataset - The Boreas dataset was collected by driving a repeated route over the course of 1 year resulting in stark seasonal variations. In total, Boreas contains over 350km of driving data including several sequences with adverse weather conditions such as rain and heavy snow. The Boreas data-taking platform features a unique high-quality sensor suite with a 128-channel Velodyne Alpha Prime lidar, a 360-degree Navtech radar, and accurate ground truth poses obtained from an Applanix POSLV GPS/IMU.

Libraries

Frameworks

Algorithms

Basic matching algorithms

Semantic segmentation

Ground segmentation

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

Object detection and object tracking

Simulators

Related awesome

Others