A Methodology Based on Lidar, Time-Of-Flight Camera and Odometry for a Real-Time 3D Model Generation

Carlos M Mesa-Cantillo; Itziar Alonso-González; David Sánchez-Rodríguez; Miguel A Quintana-Suárez; Kilian D García-Mederos

doi:10.20944/preprints202306.0303.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 4 June 2023 / Approved: 5 June 2023 / Online: 5 June 2023 (10:17:11 CEST)

This manuscript presents a system that can generate a 2D grid map and a 3D voxel model of an environment by fusing multiple sensors integrated into a robot. The fusion of these sensors is done by utilizing Robot Operating System (ROS) and some of its libraries. The sensors that are fused in the robot are a Light Detection and Ranging (LIDAR), Inertial Measurement Units (IMU), wheel encoders, and a Time-of-Flight camera. With the fusion of the point cloud data information obtained with the Time-of-Flight camera, the laser information of the LIDAR sensor, in addition to the odometry generated with the other sensors, a 2D grid map and a 3D model of two different environments were created, thus testing the performance of the system.

time-of-flight; LiDAR; indoor mapping; ROS; SLAM

Computer Science and Mathematics, Computer Vision and Graphics

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A Methodology Based on Lidar, Time-Of-Flight Camera and Odometry for a Real-Time 3D Model Generation

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