{"slug": "szenergy--awesome-lidar", "title": "Lidar", "description": "\ud83d\ude0e Awesome LIDAR list. The list includes LIDAR manufacturers, datasets, point cloud-processing algorithms, point cloud frameworks and simulators.", "github_url": "https://github.com/szenergy/awesome-lidar", "stars": "1.2K", "tag": "Hardware", "entry_count": 125, "subcategory_count": 7, "subcategories": [{"name": "General", "parent": "", "entries": [{"name": "Awesome LIDAR", "url": "#awesome-lidar-", "description": ""}, {"name": "Velodyne", "url": "https://velodynelidar.com/", "description": "Ouster and Velodyne announced the successful completion of their *merger* of equals, effective February 10, 2023. Velodyne was a mechanical and solid-state LIDAR manufacturer. The headquarter is in San Jose, California, USA."}, {"name": "Ouster", "url": "https://ouster.com/", "description": "LIDAR manufacturer, specializing in digital-spinning LiDARs. Ouster is headquartered in San Francisco, USA."}, {"name": "Livox", "url": "https://www.livoxtech.com/", "description": "LIDAR manufacturer."}, {"name": "SICK", "url": "https://www.sick.com/ag/en/", "description": "Sensor and automation manufacturer, the headquarter is located in Waldkirch, Germany."}, {"name": "Hokuyo", "url": "https://www.hokuyo-aut.jp/", "description": "Sensor and automation manufacturer, headquartered in Osaka, Japan."}, {"name": "Pioneer", "url": "http://autonomousdriving.pioneer/en/3d-lidar/", "description": "LIDAR manufacturer, specializing in MEMS mirror-based raster scanning LiDARs (3D-LiDAR). Pioneer is headquartered in Tokyo, Japan."}, {"name": "Luminar", "url": "https://www.luminartech.com/", "description": "LIDAR manufacturer focusing on compact, auto-grade sensors. Luminar is headquartered Palo Alto, California, USA."}, {"name": "Hesai", "url": "https://www.hesaitech.com/", "description": "Hesai Technology is a LIDAR manufacturer, founded in Shanghai, China."}, {"name": "Robosense", "url": "http://www.robosense.ai/", "description": "RoboSense (Suteng Innovation Technology Co., Ltd.) is a LIDAR sensor, AI algorithm and IC chipset maufactuirer based in Shenzhen and Beijing (China)."}, {"name": "LSLIDAR", "url": "https://www.lslidar.com/", "description": "LSLiDAR (Leishen Intelligent System Co., Ltd.) is a LIDAR sensor manufacturer and complete solution provider based in Shenzhen, China."}, {"name": "Ibeo", "url": "https://www.ibeo-as.com/", "description": "Ibeo Automotive Systems GmbH is an automotive industry / environmental detection laserscanner / LIDAR manufacturer, based in Hamburg, Germany."}, {"name": "Innoviz", "url": "https://innoviz.tech/", "description": "Innoviz technologies / specializes in solid-state LIDARs."}, {"name": "Quanenergy", "url": "https://quanergy.com/", "description": "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."}, {"name": "Cepton", "url": "https://www.cepton.com/index.html", "description": "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."}, {"name": "Blickfeld", "url": "https://www.blickfeld.com/", "description": "Blickfeld is a solid-state LIDAR manufacturer for autonomous mobility and IoT, based in M\u00fcnchen, Germany."}, {"name": "Neuvition", "url": "https://www.neuvition.com/", "description": "Neuvition is a solid-state LIDAR manufacturer based in Wujiang, China."}, {"name": "Aeva", "url": "https://www.aeva.com/", "description": "Aeva is bringing the next wave of perception technology to all devices for automated driving, consumer electronics, health, industrial robotics and security, Mountain View, California, USA."}, {"name": "XenomatiX", "url": "https://www.xenomatix.com/", "description": "XenomatiX offers true solid-state lidar sensors based on a multi-beam lasers concept. XenomatiX is headquartered in Leuven, Belgium."}, {"name": "MicroVision", "url": "https://microvision.com/", "description": "A pioneer in MEMS-based laser beam scanning technology, the main focus is on building Automotive grade Lidar sensors, located in Hamburg, Germany."}, {"name": "PreAct", "url": "https://www.preact-tech.com/", "description": "PreAct's mission is to make life safer and more efficient for the automotive industry and beyond. The headquarter is located in Portland, Oregon, USA."}, {"name": "Pepperl+Fuchs", "url": "https://www.pepperl-fuchs.com/", "description": "Is a global technology company, specialized in innovative automation solutions and sensor technologies, such as LiDAR, based in Mannheim, Germany."}, {"name": "Riegl", "url": "https://www.riegl.com/", "description": "Riegl is a manufacturer of 3D laser scanning systems, based in Austria."}, {"name": "Ford Dataset", "url": "https://avdata.ford.com/", "description": "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."}, {"name": "Audi A2D2 Dataset", "url": "https://www.a2d2.audi", "description": "The dataset features 2D semantic segmentation, 3D point clouds, 3D bounding boxes, and vehicle bus data."}, {"name": "Waymo Open Dataset", "url": "https://waymo.com/open/", "description": "The dataset contains independently-generated labels for lidar and camera data, not simply projections."}, {"name": "Oxford RobotCar", "url": "https://robotcar-dataset.robots.ox.ac.uk/", "description": "The Oxford RobotCar Dataset contains over 100 repetitions of a consistent route through Oxford, UK, captured over a period of over a year."}, {"name": "EU Long-term Dataset", "url": "https://epan-utbm.github.io/utbm_robocar_dataset/", "description": "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 Montb\u00e9liard in France. The vehicle speed was limited to 50 km/h following the French traffic rules."}, {"name": "NuScenes", "url": "https://www.nuscenes.org/", "description": "Public large-scale dataset for autonomous driving."}, {"name": "Lyft", "url": "https://level5.lyft.com/dataset/", "description": "Public dataset collected by a fleet of Ford Fusion vehicles equipped with LIDAR and camera."}, {"name": "KITTI", "url": "http://www.cvlibs.net/datasets/kitti/raw_data.php", "description": "Widespread public dataset, pirmarily focusing on computer vision applications, but also contains LIDAR point cloud. ![](https://img.shields.io/badge/ROS-2-34aec5?style=flat-square\\&logo=ros)"}, {"name": "Semantic KITTI", "url": "http://semantic-kitti.org/", "description": "Dataset for semantic and panoptic scene segmentation."}, {"name": "CADC - Canadian Adverse Driving Conditions Dataset", "url": "http://cadcd.uwaterloo.ca/", "description": "Public large-scale dataset for autonomous driving in adverse weather conditions (snowy weather)."}, {"name": "UofTPed50 Dataset", "url": "https://www.autodrive.utoronto.ca/uoftped50", "description": "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."}, {"name": "PandaSet Open Dataset", "url": "https://scale.com/open-datasets/pandaset", "description": "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."}, {"name": "Cirrus dataset", "url": "https://developer.volvocars.com/open-datasets/cirrus/", "description": ""}, {"name": "USyd Dataset- The Univerisity of Sydney Campus- Dataset", "url": "http://its.acfr.usyd.edu.au/datasets/usyd-campus-dataset/", "description": "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"}, {"name": "Brno Urban Dataset ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Argoverse ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Boreas Dataset", "url": "https://www.boreas.utias.utoronto.ca/", "description": "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."}, {"name": "Point Cloud Library (PCL)", "url": "http://www.pointclouds.org/", "description": "Popular highly parallel programming library, with numerous industrial and research use-cases."}, {"name": "Open3D library", "url": "http://www.open3d.org/docs/release/", "description": "Open3D library contanins 3D data processing and visualization algorithms. It is open-source and supports both C++ and Python."}, {"name": "PyTorch Geometric ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "PyTorch3d", "url": "https://pytorch3d.org/", "description": "PyTorch3d is a library for deep learning with 3D data written and maintained by the Facebook AI Research Computer Vision Team."}, {"name": "Kaolin", "url": "https://kaolin.readthedocs.io/en/latest/", "description": "Kaolin is a PyTorch Library for Accelerating 3D Deep Learning Research written by NVIDIA Technologies for game and application developers."}, {"name": "PyVista", "url": "https://docs.pyvista.org/", "description": "3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit."}, {"name": "pyntcloud", "url": "https://pyntcloud.readthedocs.io/en/latest/", "description": "Pyntcloud is a Python 3 library for working with 3D point clouds leveraging the power of the Python scientific stack."}, {"name": "pointcloudset", "url": "https://virtual-vehicle.github.io/pointcloudset/", "description": "Python library for efficient analysis of large datasets of point clouds recorded over time."}, {"name": "LAStools", "url": "https://rapidlasso.de/lastools/", "description": "C++ library and command-line tools for pointcloud processing and data compressing."}, {"name": "Autoware", "url": "https://www.autoware.ai/", "description": "Popular framework in academic and research applications of autonomous vehicles."}, {"name": "Baidu Apollo", "url": "https://apollo.auto/", "description": "Apollo is a popular framework which accelerates the development, testing, and deployment of Autonomous Vehicles."}, {"name": "ALFA Framework ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}]}, {"name": "Basic matching algorithms", "parent": "Algorithms", "entries": [{"name": "Iterative closest point (ICP) ![", "url": "https://img.shields.io/badge/youtube-red?style=flat-square\\&logo=youtube", "description": ""}, {"name": "Normal distributions transform ![", "url": "https://img.shields.io/badge/youtube-red?style=flat-square\\&logo=youtube", "description": ""}, {"name": "KISS-ICP ![", "url": "https://img.shields.io/badge/youtube-red?style=flat-square\\&logo=youtube", "description": ""}]}, {"name": "Semantic segmentation", "parent": "Algorithms", "entries": [{"name": "RangeNet++ ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "PolarNet ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "Frustum PointNets ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "Study of LIDAR Semantic Segmentation", "url": "https://larissa.triess.eu/scan-semseg/", "description": "Scan-based Semantic Segmentation of LiDAR Point Clouds: An Experimental Study IV 2020."}, {"name": "LIDAR-MOS ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "SuperPoint Graph ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "SuperPoint Transformer ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "RandLA-Net ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "Automatic labelling ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}]}, {"name": "Ground segmentation", "parent": "Algorithms", "entries": [{"name": "Plane Seg ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "LineFit Graph ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "Patchwork ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "Patchwork++ ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "GSeg3D ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}]}, {"name": "Simultaneous localization and mapping SLAM and LIDAR-based odometry and or mapping LOAM", "parent": "Algorithms", "entries": [{"name": "LOAM J. Zhang and S. Singh ![", "url": "https://img.shields.io/badge/youtube-red?style=flat-square\\&logo=youtube", "description": ""}, {"name": "LeGO-LOAM ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Cartographer ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "SuMa++ ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "OverlapNet ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "LIO-SAM ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "Removert ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "RESPLE ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "KISS-SLAM ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "FAST-LIO2 ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "MOLA ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}]}, {"name": "Object detection and object tracking", "parent": "Algorithms", "entries": [{"name": "Learning to Optimally Segment Point Clouds ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "Leveraging Heteroscedastic Aleatoric Uncertainties for Robust Real-Time LiDAR 3D Object Detection ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "What You See is What You Get: Exploiting Visibility for 3D Object Detection ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "urban\\_road\\_filter ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}, {"name": "detection\\_by\\_tracker ![", "url": "https://img.shields.io/badge/paper-blue?style=flat-square\\&logo=semanticscholar", "description": ""}]}, {"name": "LIDAR-other-sensor calibration", "parent": "Algorithms", "entries": [{"name": "direct\\_visual\\_lidar\\_calibration", "url": "https://koide3.github.io/direct_visual_lidar_calibration/", "description": "General, Single-shot, Target-less, and Automatic LiDAR-Camera Extrinsic Calibration Toolbox"}, {"name": "OpenCalib ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "CoppeliaSim", "url": "https://www.coppeliarobotics.com/coppeliaSim", "description": "Cross-platform general-purpose robotic simulator (formerly known as V-REP)."}, {"name": "OSRF Gazebo", "url": "http://gazebosim.org/", "description": "OGRE-based general-purpose robotic simulator, ROS/ROS 2 compatible."}, {"name": "CARLA", "url": "https://carla.org/", "description": "Unreal Engine based simulator for automotive applications. Compatible with Autoware, Baidu Apollo and ROS/ROS 2."}, {"name": "LGSVL / SVL", "url": "https://www.lgsvlsimulator.com/", "description": "Unity Engine based simulator for automotive applications. Compatible with Autoware, Baidu Apollo and ROS/ROS 2. *Note:* LG has made the difficult decision to [suspend](https://www.svlsimulator.com/news/2022-01-20-svl-simulator-sunset) active development of SVL Simulator."}, {"name": "OSSDC SIM", "url": "https://github.com/OSSDC/OSSDC-SIM", "description": "Unity Engine based simulator for automotive applications, based on the suspended LGSVL simulator, but an active development. Compatible with Autoware, Baidu Apollo and ROS/ROS 2.", "stars": "87"}, {"name": "AirSim", "url": "https://microsoft.github.io/AirSim", "description": "Unreal Engine based simulator for drones and automotive. Compatible with ROS."}, {"name": "AWSIM", "url": "https://tier4.github.io/AWSIM", "description": "Unity Engine based simulator for automotive applications. Compatible with Autoware and ROS 2."}, {"name": "Awesome point cloud analysis ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Awesome robotics ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Awesome robotics libraries ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Awesome ROS 2 ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Awesome artificial intelligence ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Awesome computer vision ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Awesome machine learning ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Awesome deep learning ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Awesome reinforcement learning ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Awesome SLAM datasets ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Awesome electronics ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Awesome vehicle security and car hacking ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Awesome LIDAR-Camera calibration ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Awesome LiDAR Place Recognition ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Awesome-LiDAR-MOS ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Awesome-LiDAR-Visual-SLAM ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Awesome LIDAR ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "ARHeadsetKit", "url": "https://github.com/philipturner/ARHeadsetKit", "description": "Using $5 Google Cardboard to replicate Microsoft Hololens. Hosts the source code for research on [scene color reconstruction (\u2b5025)](https://github.com/philipturner/scene-color-reconstruction).", "stars": "129"}, {"name": "Pointcloudprinter ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "CloudCompare", "url": "https://cloudcompare.org/", "description": "CloudCompare is a free, cross-platform point cloud editor software."}, {"name": "Pcx ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Bpy ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Semantic Segmentation Editor ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "3D Bounding Box Annotation Tool ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Photogrammetry importer ![", "url": "https://img.shields.io/badge/github-black?style=flat-square\\&logo=github", "description": ""}, {"name": "Foxglove", "url": "https://foxglove.dev/", "description": "Foxglove Studio is an integrated visualization and diagnosis tool for robotics, available in your browser or for download as a desktop app on Linux, Windows, and macOS."}, {"name": "Lichtblick suite", "url": "https://github.com/lichtblick-suite", "description": "Lichtblick is an open-source alternative to Foxglove Studio for visualizing and analyzing robotics data."}, {"name": "Rerun", "url": "https://rerun.io/", "description": "Rerun is a tool for time-aware multimodal data stack and visualizations."}, {"name": "MeshLab", "url": "https://www.meshlab.net/", "description": "MeshLab is an open source, portable, and extensible system for the processing and editing 3D triangular meshes and pointcloud."}, {"name": "CloudPeek", "url": "https://github.com/Geekgineer/CloudPeek", "description": "", "stars": "126"}, {"name": "Which SLAM Algorithm Should I Choose?", "url": "https://www.slambotics.org/blog/which-slam-to-choose", "description": ""}]}], "name": ""}