LiDAR-GEiL: LiDAR GPU Exploitation in Lightsimulations

Manuel Vogel, Maximilian Kunz, Eike Gassen, Karsten Berns

2023

Abstract

We propose a novel Light Detection And Ranging (LiDAR) simulation method using Unreal Engine’s Niagara particle system. Instead of performing the ray traces sequentially on the CPU or transforming depth images into point clouds, our method performs this particle-based approach using GPU particles that execute one line trace each. Due to execution on the GPU, it is very fast-performing. In order to classify the results, the new implementation is compared to existing ray-tracing and camera-based LiDAR. In addition to that we implemented and compared common LiDAR approaches using ray-tracing as well as depth images using cameras. A general architecture for easy exchange between simulated sensors and their communication is given using the adapter pattern. As a benchmark, we evaluated real sensor data with a ray tracing-based virtual sensor.

Paper Citation

in Harvard Style

Vogel M., Kunz M., Gassen E. and Berns K. (2023). LiDAR-GEiL: LiDAR GPU Exploitation in Lightsimulations. In Proceedings of the 13th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH; ISBN 978-989-758-668-2, SciTePress, pages 71-81. DOI: 10.5220/0012085900003546

in Bibtex Style

@conference{simultech23,
author={Manuel Vogel and Maximilian Kunz and Eike Gassen and Karsten Berns},
title={LiDAR-GEiL: LiDAR GPU Exploitation in Lightsimulations},
booktitle={Proceedings of the 13th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH},
year={2023},
pages={71-81},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012085900003546},
isbn={978-989-758-668-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH
TI - LiDAR-GEiL: LiDAR GPU Exploitation in Lightsimulations
SN - 978-989-758-668-2
AU - Vogel M.
AU - Kunz M.
AU - Gassen E.
AU - Berns K.
PY - 2023
SP - 71
EP - 81
DO - 10.5220/0012085900003546
PB - SciTePress