Analytical Formalism for Data Representation and Object Detection with 2D LiDAR

Analytical Formalism for Data Representation and Object Detection with 2D LiDAR: Application in Mobile Robotics

Fagundes Jr, L. A., Caldeira, A. G., Quemelli, M. B., Martins, F. N., & Brandão, A. S.

Sensors, 24(7), 2284. Publication year: 2024

Abstract
In mobile robotics, LASER scanners have a wide spectrum of indoor and outdoor applications, both in structured and unstructured environments, due to their accuracy and precision. Most works that use this sensor have their own data representation and their own case-specific modeling strategies, and no common formalism is adopted. To address this issue, this manuscript presents an analytical approach for the identification and localization of objects using 2D LiDARs. Our main contribution lies in formally defining LASER sensor measurements and their representation, the identification of objects, their main properties, and their location in a scene. We validate our proposal with experiments in generic semi-structured environments common in autonomous navigation, and we demonstrate its feasibility in multiple object detection and identification, strictly following its analytical representation. Finally, our proposal further encourages and facilitates the design, modeling, and implementation of other applications that use LASER scanners as a distance sensor.

Keywords: LASER scanner; LiDAR; object detection; object localization; mobile robotics

Read our manuscript at: https://doi.org/10.3390/s24072284

Chapters:
0:00 Introduction
0:50 Object Detection and Mapping

Cite us with following bibtex:

@article{fagundes2024analytical,
title={Analytical Formalism for Data Representation and Object Detection with 2D LiDAR: Application in Mobile Robotics},
author={Fagundes Jr, Leonardo A and Caldeira, Alexandre G and Quemelli, Matheus B and Martins, Felipe N and Brand{\~a}o, Alexandre S},
journal={Sensors},
volume={24},
number={7},
pages={2284},
year={2024},
publisher={MDPI}
}