Integrating a LiDAR Sensor in a UAV Platform to Obtain a Georeferenced Point Cloud

• Autores: Del Savio, Alexandre Almeida, Luna Torres, Ana Felícita, Chicchón Apaza, Miguel Ángel, Vergara Olivera, Mónica Alejandra, Llimpe Rojas, Rocio Sara, Urday Ibarra, Gianella Tania, Reyes Ñique, José Luis, Macedo Arevalo, Rolando Issac
• Formato: artículo
• Fecha de Publicación: 2022
• Institución: Universidad de Lima
• Repositorio: ULIMA-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.ulima.edu.pe:20.500.12724/17649
• Enlace del recurso: https://hdl.handle.net/20.500.12724/17649; https://doi.org/10.3390/app122412838
• Nivel de acceso: acceso abierto
• Materia: Aerial photogrammetry; Surveying; Drones; Fotogrametría aérea; Topografía; https://purl.org/pe-repo/ocde/ford#2.01.01

The combination of light detection and ranging (LiDAR) sensors and unmanned aerial vehicle (UAV) platforms have garnered considerable interest in recent years because of the wide range of applications performed through the generation of point clouds, such as surveying, building layouts and infrastructure inspection. The attributed benefits include a shorter execution time and higher accuracy when surveying and georeferencing infrastructure and building projects. This study seeks to develop, integrate and use a LiDAR sensor system implemented in a UAV to collect topography data and propose a procedure for obtaining a georeferenced point cloud that can be configured according to the user’s needs. A structure was designed and built to mount the LiDAR system components to the UAV. Survey tests were performed to determine the system’s accuracy. An open-source ROS package was used to acquire data and generate point clouds. The results were compared against a photogrammetric survey, denoting a mean squared error of 17.1 cm in survey measurement reliability and 76.6 cm in georeferencing reliability. Therefore, the developed system can be used to reconstruct extensive topographic environments and large-scale infrastructure in which a presentation scale of 1/2000 or more is required, due to the accuracy obtained in the work presented.