OpenSimpleLidar - Open Hardware scanning laser rangefinder

•    C

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Open Hardware scanning laser rangefinder. It is really cheap - its components cost less than $35.

lidar stm32 ros diy

lopocs - Light OpenSource PointCloud Server

•    Python

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LOPoCS is a point cloud server written in Python, allowing to load Point Cloud from a PostgreSQL database thanks to the pgpointcloud extension. Note that LOPoCS is currently the only 3DTiles server able to stream data from pgpointcloud. This is possible thanks to the python module py3dtiles.

pointcloud 3d gis lidar opensource itowns cesiumjs postgis

lidR - R package for airborne LiDAR data manipulation and visualisation for forestry application

•    R

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The lidR package provides functions to read and write .las and .laz files, plot point clouds, compute metrics using an area-based approach, compute digital canopy models, thin lidar data, manage a catalog of datasets, automatically extract ground inventories, process a set of tiles using multicore processing, individual tree segmentation, classify data from geographic data, and provides other tools to manipulate LiDAR data in a research and development context. Development of the lidR package between 2015 and 2018 was made possible thanks to the financial support of the AWARE project (NSERC CRDPJ 462973-14); grantee Prof Nicholas Coops.

point-cloud lidar las laz r als lidar-data-manipulation

rlas - R package to read and write las and laz files used to store LiDAR data

•    C++

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R package to read and write .las and .laz binary files used to store LiDAR data. rlas relies on a modified version of the open source parts of LAStools. LASlib and LASzip were modified to be compatible with R. The library can therefore be compiled into R without any complaints from R CMD check. It enables users to read and write into R binary files commonly used to store LiDAR data in R both at the R level and at the C++ level.

las asprs laz lidar r

open-basemap - More details at:

•    Lasso

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Open Basemap is a collaborative initiative towards enabling worldwide autonomous vehicle development. More information can be found here. Besides git you will also need to setup git-lfs on your system by following the instructions here.

autonomous-vehicles self-driving-cars perception path-planning localization semantic-maps 3d-map lidar robotics maps

displaz - A hackable lidar viewer

•    C++

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displaz is a cross platform viewer for displaying lidar point clouds and derived artifacts such as fitted meshes. The interface was originally developed for viewing large airborne laser scans, but also works quite well for point clouds acquired using terrestrial lidar and other sources such as bathymetric sonar. The goal is to provide a flexible and programmable technical tool for exploring large lidar point data sets and derived geometry.

geospatial lidar point-cloud

OpenLIDAR - Open Hardware scanning triangulation laser rangefinder

•    C

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Simple enough scanning laser rangefinder. Based on triangulation method. Used STM32F303 + ELIS-1024 sensor.

laser rangefinder lidar

lidario - A small Go library for reading and writing LiDAR (LAS) files

•    Go

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lidario is a simple library for reading and writing LiDAR files stored in LAS format. The library is written using the Go programing language. Use the build.py file to build/install the source code. The script can also be used to run the tests.

lidar gis-data gis las

uavRst - UAV related Remote Sensing Toolbox

•    R

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The uavRmp package provides functions for rtf-UAV based autonomous mission planning. In the first place it is a simple and open source planning tool to plan autonomous terrainfollowing monitoring flights of low budget drones based on R. It provides an easy workflow for survey planning including battery-dependent task splitting, obstacle avoiding departures, and approaches of each monitoring chunks or spatial position. The uavRstanalysis toolbox package is far from being mature. You will need for most of the uavRst functions a bunch of third party software. The most comfortable way to fulfill these requirements is to install QGIS, GRASS- and SAGA-GIS. Following the excellent provided by the RQGIS team will give you a good first try to ensure a smooth working environment.

r lidar aerial-imagery uav remote-sensing forestry machine-learning giscience

helios - HELIOS - the Heidelberg LiDAR Operations Simulator - is a software package for interactive real-time simulation and visualisation of terrestrial, mobile and airborne laser scan surveys written in Java

•    Java

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The pre-built project is available here with a test scene and survey. Note that for faster simulations building the project is recommended. To build the project, first install the dependencies, then compile the source code, and finally execute it.

gis lidar lidar-point-cloud 3d simulation jmonkeyengine interactive-visualizations visualization

opendlv - OpenDLV - A modern microservice-based software ecosystem for self-driving vehicles.

•    CMake

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Applications based on OpenDLV are grouped in UDP multicast sessions belonging to IPv4 address 225.0.0.X, where X is from the within the range [1,254]. All microservices belonging to the same UDP multicast group are able to communicate with each other; thus, two applications running in different UDP multicast sessions do not see each other and are completely separated. The actual UDP multicast session is selected using the commandline parameter --cid=111, where 111 would define the UDP multicast address 225.0.0.111. Microservices exchange data using the message Envelope that contains besides the actual message to send further meta information like sent and received timestamp and the point in time when the contained message was actually sampled. All messages are encoded in Google's Protobuf data format (example) that has been adjusted to preserve forwards and backwards compatibility using libcluon's native implementation of Protobuf.

opendlv libcluon cpp14 microservice docker self-driving-car autonomous-driving amd64 armhf aarch64 trimble-gps gps nmea oxts-gps velodyne lidar applanix video4linux openh264 h264

whitebox - A Python package for advanced geospatial data analysis

•    Python

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A Python package for advanced geospatial data analysis. This page is related to the whitebox Python package for geospatial analysis, which is built on a stand-alone executable command-line program called WhiteboxTools.

geospatial gis remote-sensing geoprocessing hydrology geomorphometry geomorphology lidar

hdl_graph_slam - 3D LIDAR-based Graph SLAM

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hdl_graph_slam is an open source ROS package for real-time 3D slam using a 3D LIDAR. It is based on 3D Graph SLAM with NDT scan matching-based odometry estimation and loop detection. It also utilizes floor plane detection to generate an environmental map with a completely flat floor. We have tested this packaged mainly in indoor environments, but it can be applied to outdoor environment mapping as well. hdl_graph_slam consists of four nodelets.

ros slam lidar velodyne hdl-graph-slam point-cloud rslidar

hdl_localization - Real-time 3D localization using a (velodyne) 3D LIDAR

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hdl_localization is a ROS package for real-time 3D localization using a 3D LIDAR, such as velodyne HDL32e and VLP16. This package performs Unscented Kalman Filter-based pose estimation. It first estimates the sensor pose from IMU data implemented on the LIDAR, and then performs multi-threaded NDT scan matching between a globalmap point cloud and input point clouds to correct the estimated pose. IMU-based pose prediction is optional. If you disable it, the system predicts the sensor pose with the constant velocity model without IMU information. All parameters are listed in launch/hdl_localization.launch as ros params. You can specify the initial sensor pose using "2D Pose Estimate" on rviz, or using ros params (see example launch file).

localization ros lidar real-time velodyne

hdl_people_tracking - Real-time people tracking using a 3D LIDAR

•    C++

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hdl_people_tracking is a ROS package for real-time people tracking using a 3D LIDAR. It first performs Haselich's clustering technique to detect human candidate clusters, and then applies Kidono's person classifier to eliminate false detections. The detected clusters are tracked by using Kalman filter with a contant velocity model. If it doesn't work well, change ndt_neighbor_search_method in hdl_localization.launch to "DIRECT1". It makes the scan matching significantly fast, but a little bit unstable.

ros lidar velodyne person-tracking human-detection