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.
- Any list item with an 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
- Velodyne – Velodyne is a mechanical and solid-state LIDAR manufacturer. The headquarter is in San Jose, California, USA.
- Ouster – LIDAR manufacturer, specializing in digital-spinning LiDARs. Ouster is headquartered in San Francisco, USA.
- Livox – LIDAR manufacturer.
- SICK – Sensor and automation manufacturer, the headquarter is located in Waldkirch, Germany.
- Hokuyo – Sensor and automation manufacturer, headquartered in Osaka, Japan.
- Pioneer – LIDAR manufacturer, specializing in MEMS mirror-based raster scanning LiDARs (3D-LiDAR). Pioneer is headquartered in Tokyo, Japan.
- Luminar – LIDAR manufacturer focusing on compact, auto-grade sensors. Luminar is headquartered Palo Alto, California, USA.
- Hesai – Hesai Technology is a LIDAR manufacturer, founded in Shanghai, China.
- Robosense – RoboSense (Suteng Innovation Technology Co., Ltd.) is a LIDAR sensor, AI algorithm and IC chipset maufactuirer based in Shenzhen and Beijing (China).
- Ibeo – Ibeo Automotive Systems GmbH is an automotive industry / environmental detection laserscanner / LIDAR manufacturer, based in Hamburg, Germany.
- Innoviz – Innoviz technologies / specializes in solid-state LIDARs.
- Quanenergy – Quanenergy Systems / solid-state and mechanical LIDAR sensors / offers End-to-End solutions in Mapping, Industrial Automation, Transportation and Security. The headquarter is located in Sunnyvale, California, USA.
- Cepton – Cepton (Cepton Technologies, Inc.) / pioneers in frictionless, and mirrorless design, self-developed MMT (micro motion technology) lidar technology. The headquarter is located in San Jose, California, USA.
- Blickfeld – Blickfeld is a solid-state LIDAR manufacturer for autonomous mobility and IoT, based in München, Germany.
- Neuvition – Neuvition is a solid-state LIDAR manufacturer based in Wujiang, China.
- 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.
- Point Cloud Library (PCL) – Popular highly parallel programming library, with numerous industrial and research use-cases.
- Open3D library – Open3D library contanins 3D data processing and visualization algorithms. It is open-source and supports both C++ and Python.
- PyTorch Geometric 📰 – A geometric deep learning extension library for PyTorch.
- PyTorch3d – PyTorch3d is a library for deep learning with 3D data written and maintained by the Facebook AI Research Computer Vision Team.
- Kaolin – Kaolin is a PyTorch Library for Accelerating 3D Deep Learning Research written by NVIDIA Technologies for game and application developers.
- PyVista – 3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit.
- pyntcloud – Pyntcloud is a Python 3 library for working with 3D point clouds leveraging the power of the Python scientific stack.
- Autoware – Popular framework in academic and research applications of autonomous vehicles.
- Baidu Apollo – Apollo is a popular framework which accelerates the development, testing, and deployment of Autonomous Vehicles.
Basic matching algorithms
- Iterative closest point 🔴 – The must-have algorithm for feature matching applications (ICP).
- Normal distributions transform 🔴 – More recent massively-parallel approach to feature matching (NDT).
- RangeNet++ 📰 – Fast and Accurate LiDAR Sematnic Segmentation with fully convolutional network.
- PolarNet 📰 – An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation.
- Frustum PointNets 📰 – Frustum PointNets for 3D Object Detection from RGB-D Data.
- Study of LIDAR Semantic Segmentation – Scan-based Semantic Segmentation of LiDAR Point Clouds: An Experimental Study IV 2020.
Simultaneous localization and mapping SLAM and LIDAR-based odometry and or mapping LOAM
- LOAM J. Zhang and S. Singh 🔴 – LOAM: Lidar Odometry and Mapping in Real-time.
- LeGO-LOAM – A lightweight and ground optimized lidar odometry and mapping (LeGO-LOAM) system for ROS compatible UGVs.
- Cartographer – Cartographer is ROS compatible system that provides real-time simultaneous localization and mapping (SLAM) in 2D and 3D across multiple platforms and sensor configurations.
- SuMa++ 📰 – LiDAR-based Semantic SLAM.
- OverlapNet 📰 – Loop Closing for LiDAR-based SLAM.
- LIO-SAM 📰 – Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping.
Object detection and object tracking
- Learning to Optimally Segment Point Clouds 📰 – By Peiyun Hu, David Held, and Deva Ramanan at Carnegie Mellon University. IEEE Robotics and Automation Letters, 2020.
- Leveraging Heteroscedastic Aleatoric Uncertainties for Robust Real-Time LiDAR 3D Object Detection 📰 – By Di Feng, Lars Rosenbaum, Fabian Timm, Klaus Dietmayer. 30th IEEE Intelligent Vehicles Symposium, 2019.
- What You See is What You Get: Exploiting Visibility for 3D Object Detection 📰 – By Peiyun Hu, Jason Ziglar, David Held, Deva Ramanan, 2019.
- CoppeliaSim – Cross-platform general-purpose robotic simulator (formerly known as V-REP).
- OSRF Gazebo – OGRE-based general-purpose robotic simulator, ROS/ROS2 compatible.
- CARLA – Unreal Engine based simulator for automotive applications. Compatible with Autoware, Baidu Apollo and ROS/ROS2.
- LGSVL – Unity Engine based simulator for automotive applications. Compatible with Autoware, Baidu Apollo and ROS/ROS2.
- AirSim – Unreal Engine based simulator for drones and automotive. Compatible with ROS.
- Pointcloudprinter – A tool to turn point cloud data from aerial lidar scans into solid meshes for 3D printing.
- Pcx – Point cloud importer/renderer for Unity.
- Bpy – Point cloud importer/renderer/editor for Blender, Point Cloud visualizer.
- Semantic Segmentation Editor – Point cloud and image semantic segmentation editor by Hitachi Automotive And Industry Laboratory.
- Photogrammetry importer – Blender addon to import reconstruction results of several libraries.