Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Object Detection in Robot Autonomous Navigation Using 2D LiDAR Data: An Analytical Approach

Leonardo Alves Fagundes-Junior
ORCID logo ,
Alexandre Gomes Caldeira
ORCID logo ,
Matheus Berguer Quemelli
,
Felipe N. Martins
ORCID logo ,
Alexandre Santos Brandão
* ORCID logo
Version 1 : Received: 4 January 2024 / Approved: 22 January 2024 / Online: 23 January 2024 (05:01:31 CET)

A peer-reviewed article of this Preprint also exists.

Fagundes, L.A., Jr.; Caldeira, A.G.; Quemelli, M.B.; Martins, F.N.; Brandão, A.S. Analytical Formalism for Data Representation and Object Detection with 2D LiDAR: Application in Mobile Robotics. Sensors 2024, 24, 2284. Fagundes, L.A., Jr.; Caldeira, A.G.; Quemelli, M.B.; Martins, F.N.; Brandão, A.S. Analytical Formalism for Data Representation and Object Detection with 2D LiDAR: Application in Mobile Robotics. Sensors 2024, 24, 2284.

Abstract

In mobile robotics, laser scanners have a wide spectrum of indoor and outdoor applications, both in structured and unstructured environments, due its 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 identification and localization of objects using a 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 on multiple object detection and identification, following strictly 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; object detection; object localization; mobile robotics; LiDAR

Subject

Engineering, Electrical and Electronic Engineering

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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