@conference {cGarcia-Gomez22,
	title = {Multimodal imaging System based on s{\`o}lid-State LiDAR for Advanced perception applications},
	booktitle = {10th International Symposium on Optronics in defence \& security},
	year = {2022},
	month = {06/2022},
	publisher = {3AF OPTRO2022},
	organization = {3AF OPTRO2022},
	address = {Versailles, France},
	url = {https://www.3af-optro.com/},
	author = {Pablo Garc{\'\i}a-G{\'o}mez and S. Royo and Noel Rodrigo and Casas, J. and Jordi Riu}
}
@conference {cGarcia-Gomez21,
	title = {Multimodal solid-state LiDAR for advanced perception applications},
	booktitle = {OPTOEL},
	year = {2021},
	month = {06/2021},
	abstract = {<p>Perception of the environment is an essential requirement for the fields of autonomous vehicles and robotics. Consequently, LiDAR imaging sensors have become crucial sen-sors for such applications due to their 3D geometry sensing capability. However, auton-omous systems claim for high amounts of data to make reliable decisions so many dif-ferent sensors are often combined. In this context, we present a multimodal imaging sys-tem based on a solid-state LiDAR combined with three other imaging sensors that pro-vides multimodal information with low parallax fusion error.</p>},
	keywords = {artificial intelligence, autonomous navigation, computer Vision, enhanced perception, robotics, sensor fusion, solid-state LiDAR},
	author = {Pablo Garc{\'\i}a-G{\'o}mez and Noel Rodrigo and Jordi Riu and Casas, J. and S. Royo}
}
@article {aGarcia-Gomez20,
	title = {Geometric Model and Calibration Method for a Solid-State LiDAR},
	journal = {Sensors},
	volume = {20},
	year = {2020},
	month = {05/2020},
	pages = {2898},
	abstract = {<p>This paper presents a novel calibration method for solid-state LiDAR devices based on a geometrical description of their scanning system, which has variable angular resolution. Determining this distortion across the entire Field-of-View of the system yields accurate and precise measurements which enable it to be combined with other sensors. On the one hand, the geometrical model is formulated using the well-known Snell{\textquoteright}s law and the intrinsic optical assembly of the system, whereas on the other hand the proposed method describes the scanned scenario with an intuitive camera-like approach relating pixel locations with scanning directions. Simulations and experimental results show that the model fits with real devices and the calibration procedure accurately maps their variant resolution so undistorted representations of the observed scenario can be provided. Thus, the calibration method proposed during this work is applicable and valid for existing scanning systems improving their precision and accuracy in an order of magnitude.</p>},
	keywords = {solid-state LiDAR; LiDAR calibration; distortion correction; FOV mapping},
	issn = {1424-8220},
	doi = {10.3390/s20102898},
	url = {https://www.mdpi.com/1424-8220/20/10/2898},
	author = {Pablo Garc{\'\i}a-G{\'o}mez and S. Royo and Noel Rodrigo and Casas, J.}
}
