š Awesome LIDAR list. The list includes LIDAR manufacturers, datasets, point cloud-processing algorithms, point cloud frameworks and simulators.
This page lists names, links and short descriptions. The original list on GitHub is the source and belongs to its authors.
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, simulatorsā¦
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.
A collection of ROS packages supporting Velodyne high definition 3D LIDARs.
LIDAR manufacturer, specializing in digital-spinning LiDARs. Ouster is headquartered in San Francisco, USA.
LIDAR manufacturer.
Sensor and automation manufacturer, the headquarter is located in Waldkirch, Germany.
Sensor and automation manufacturer, headquartered in Osaka, Japan.
LIDAR manufacturer, specializing in MEMS mirror-based raster scanning LiDARs (3D-LiDAR). Pioneer is headquartered in Tokyo, Japan.
LIDAR manufacturer focusing on compact, auto-grade sensors. Luminar is headquartered Palo Alto, California, USA.
Hesai Technology is a LIDAR manufacturer, founded in Shanghai, China.
RoboSense (Suteng Innovation Technology Co., Ltd.) is a LIDAR sensor, AI algorithm and IC chipset maufactuirer based in Shenzhen and Beijing (China).
LSLiDAR (Leishen Intelligent System Co., Ltd.) is a LIDAR sensor manufacturer and complete solution provider based in Shenzhen, China.
Ibeo Automotive Systems GmbH is an automotive industry / environmental detection laserscanner / LIDAR manufacturer, based in Hamburg, Germany.
Innoviz technologies / specializes in solid-state LIDARs.
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 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 is a solid-state LIDAR manufacturer for autonomous mobility and IoT, based in MĆ¼nchen, Germany.
Neuvition is a solid-state LIDAR manufacturer based in Wujiang, China.
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.
XenomatiX offers true solid-state lidar sensors based on a multi-beam lasers concept. XenomatiX is headquartered in Leuven, Belgium.
A pioneer in MEMS-based laser beam scanning technology, the main focus is on building Automotive grade Lidar sensors, located in Hamburg, Germany.
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.
Is a global technology company, specialized in innovative automation solutions and sensor technologies, such as LiDAR, based in Mannheim, Germany.
Riegl is a manufacturer of 3D laser scanning systems, based in Austria.
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.
The dataset features 2D semantic segmentation, 3D point clouds, 3D bounding boxes, and vehicle bus data.
The dataset contains independently-generated labels for lidar and camera data, not simply projections.
The Oxford RobotCar Dataset contains over 100 repetitions of a consistent route through Oxford, UK, captured over a period of over a year.
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 MontbƩliard in France. The vehicle speed was limited to 50 km/h following the French traffic rules.
Public large-scale dataset for autonomous driving.
Public dataset collected by a fleet of Ford Fusion vehicles equipped with LIDAR and camera.
Widespread public dataset, pirmarily focusing on computer vision applications, but also contains LIDAR point cloud.
Dataset for semantic and panoptic scene segmentation.
Public large-scale dataset for autonomous driving in adverse weather conditions (snowy weather).
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.
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.
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.
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
Navigation and localisation dataset for self driving cars and autonomous robots in Brno, Czechia.
A dataset designed to support autonomous vehicle perception tasks including 3D tracking and motion forecasting collected in Pittsburgh, Pennsylvania and Miami, Florida, USA.
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-takingā¦
Popular highly parallel programming library, with numerous industrial and research use-cases.
Standalone, large-scale open project for 2D/3D image and point cloud processing. Comprehensive algorithms for filtering, feature estimation, surface reconstruction, registration, model fitting, and segmentation. BSD licensed.
Open3D library contanins 3D data processing and visualization algorithms. It is open-source and supports both C++ and Python.
Open3D: A Modern Library for 3D Data Processing.
A geometric deep learning extension library for PyTorch.
is a geometric deep learning extension library for PyTorch.
PyTorch3d is a library for deep learning with 3D data written and maintained by the Facebook AI Research Computer Vision Team.
FAIR's library of reusable components for deep learning with 3D data. Provides efficient 3D operators, differentiable rendering, and mesh processing tools integrated with PyTorch. BSD licensed.
Kaolin is a PyTorch Library for Accelerating 3D Deep Learning Research written by NVIDIA Technologies for game and application developers.
PyTorch library aimed at accelerating 3D deep learning research
3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit.
3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK).
Pyntcloud is a Python 3 library for working with 3D point clouds leveraging the power of the Python scientific stack.
Python library for efficient analysis of large datasets of point clouds recorded over time.
C++ library and command-line tools for pointcloud processing and data compressing.
Award-winning software for efficient LiDAR processing.
C++20 and C library for reading and writing LAS, LAZ and COPC with parallel LAZ decoding, built on the Rust crates las-rs and laz-rs.
Popular framework in academic and research applications of autonomous vehicles.
Provides test environment for Autoware and still during early development, contents below may changed during updates.
Apollo is a popular framework which accelerates the development, testing, and deployment of Autonomous Vehicles.
High performance, flexible architecture which accelerates the development, testing, and deployment of Autonomous Vehicles.
An open-source framework for developing processing algorithms, with a focus on embedded platforms and hardware acceleration.
The must-have algorithm for feature matching applications (ICP).
simpleICP C++ /Julia / Matlab / Octave / Python implementation.
libpointmatcher, a modular library implementing the ICP algorithm.
libpointmatcher: Comparing ICP variants on real-world data sets.
More recent massively-parallel approach to feature matching (NDT).
In Defense of Point-to-Point ICP ā Simple, Accurate, and Robust Registration If Done the Right Way.
A LiDAR Odometry pipeline that just works on most of the cases without tunning any parameter.
Fast and Accurate LiDAR Sematnic Segmentation with fully convolutional network.
Contains simple usage explanations of how the RangeNet++ inference works with the TensorRT and C++ interface.
An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation.
An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation.
Frustum PointNets for 3D Object Detection from RGB-D Data.
Scan-based Semantic Segmentation of LiDAR Point Clouds: An Experimental Study IV 2020.
Moving Object Segmentation in 3D LIDAR Data
Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs
Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs.
Efficient 3D Semantic Segmentation with Superpoint Transformer
Efficient Semantic Segmentation of Large-Scale Point Clouds
Efficient Semantic Segmentation of Large-Scale Point Clouds.
Automatic labelling of urban point clouds using data fusion
ROS comapatible ground plane segmentation; a library for fitting planes to LIDAR.
Line fitting-based fast ground segmentation for horizontal 3D LiDAR data
Implementation of the ground segmentation algorithm.
Region-wise plane fitting-based robust and fast ground segmentation for 3D LiDAR data
Improved version of Patchwork. Patchwork++ provides pybinding as well for deep learning users
High-precision grid-based ground segmentation for LiDAR point clouds designed for safety-critical robotics and autonomous driving.
LOAM: Lidar Odometry and Mapping in Real-time.
A lightweight and ground optimized lidar odometry and mapping (LeGO-LOAM) system for ROS compatible UGVs.; ROS 2 verison on different repo: GitHub repository
Cartographer is ROS compatible system that provides real-time simultaneous localization and mapping (SLAM) in 2D and 3D across multiple platforms and sensor configurations.
LiDAR-based Semantic SLAM.
Semantic Mapping using Surfel Mapping and Semantic Segmentation.
Loop Closing for LiDAR-based SLAM.
A modified Siamese Network that predicts the overlap and relative yaw angle of a pair of range images generated by 3D LiDAR scans.
Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping.
A real-time lidar-inertial odometry package with very promising results for multi-beam LiDARS. Licence: BSD-3 Clause.
Remove, then Revert: Static Point cloud Map Construction using Multiresolution Range Images.
Remove then revert. Static map construction in the wild and dynamic points removing tool by constructing a static map.
Recursive Spline Estimation for LiDAR-Based Odometry
KISS-SLAM is a simple, robust, and accurate 3D LiDAR SLAM system that just works.
Fast LiDAR-Inertial Odometry is a computationally efficient and robust LiDAR-inertial odometry package
A computationally efficient and robust LiDAR-inertial odometry (LIO) package
Modular system for Localization and Mapping, providing LiDAR Odometry (LO), LiDAR-inertial Odometry (LIO), SLAM, localization-only modes, and geo-referencing.
A Modular System for Localization and Mapping.
By Peiyun Hu, David Held, and Deva Ramanan at Carnegie Mellon University. IEEE Robotics and Automation Letters, 2020.
By Di Feng, Lars Rosenbaum, Fabian Timm, Klaus Dietmayer. 30th IEEE Intelligent Vehicles Symposium, 2019.
By Peiyun Hu, Jason Ziglar, David Held, Deva Ramanan, 2019.
Real-Time LIDAR-Based Urban Road and Sidewalk Detection for Autonomous Vehicles
Real-time LIDAR-based Urban Road and Sidewalk detection for Autonomous Vehicles.
3D-LIDAR Multi Object Tracking for Autonomous Driving: Multi-target Detection and Tracking under Urban Road Uncertainties, also used in Autoware Universe
General, Single-shot, Target-less, and Automatic LiDAR-Camera Extrinsic Calibration Toolbox
A toolbox for target-less LiDAR-camera calibration [ROS1/ROS2]
A Multi-sensor Calibration Toolbox for Autonomous Driving
Cross-platform general-purpose robotic simulator (formerly known as V-REP).
OGRE-based general-purpose robotic simulator, ROS/ROS 2 compatible.
Robotics simulator often used for planetary rovers
Unreal Engine based simulator for automotive applications. Compatible with Autoware, Baidu Apollo and ROS/ROS 2.
is an open-source simulator for autonomous driving research. CARLA has been developed from the ground up to support development, training, and validation of autonomous driving systems. In addition to open-source code and protocols, CARLA provides open digital assets (urban layouts, buildings,ā¦
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 active development of SVL Simulator.
LG Electronics America R&D Center has developed an HDRP Unity-based multi-robot simulator for autonomous vehicle developers.
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.
Unreal Engine based simulator for drones and automotive. Compatible with ROS.
Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
Unity Engine based simulator for automotive applications. Compatible with Autoware and ROS 2.
Using $5 Google Cardboard to replicate Microsoft Hololens. Hosts the source code for research on scene color reconstruction.
A tool to turn point cloud data from aerial lidar scans into solid meshes for 3D printing.
CloudCompare is a free, cross-platform point cloud editor software.
Point cloud importer/renderer for Unity.
Point cloud importer/renderer/editor for Blender, Point Cloud visualizer.
Point cloud and image semantic segmentation editor by Hitachi Automotive And Industry Laboratory, point cloud annotator / labeling.
3D BAT: A Semi-Automatic, Web-based 3D Annotation Toolbox for Full-Surround, Multi-Modal Data Streams, point cloud annotator / labeling.
Blender addon to import reconstruction results of several libraries.
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.
Web and desktop app for robotics visualization and debugging; actively maintained fork of webviz.
Lichtblick is an open-source alternative to Foxglove Studio for visualizing and analyzing robotics data.
Rerun is a tool for time-aware multimodal data stack and visualizations.
An SDK for logging computer vision and robotics data paired with a visualizer for exploring that data over time. It lets you debug and understand the internal state and data of your systems with minimal code. Licence: Dual licence under MIT OR Apache-2.0.
MeshLab is an open source, portable, and extensible system for the processing and editing 3D triangular meshes and pointcloud.
MeshLab is an open source, portable, and extensible system for the processing and editing of unstructured large 3D triangular meshes
is a lightweight, c++ single-header, cross-platform point cloud viewer, designed for simplicity and efficiency without relying on heavy external libraries like PCL or Open3D.
Slambotics - Choosing the Right SLAM Algorithm
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