Comparison of Trajectory Estimation Methods Based on LIDAR and Monocular Camera in a Simulated Environment

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Standard

Comparison of Trajectory Estimation Methods Based on LIDAR and Monocular Camera in a Simulated Environment. / Evangelista, Amanda Dias; Schettino, Vinícius Barbosa; dos Santos, Murillo Ferreira et al.
Proceedings of the 2024 25th International Carpathian Control Conference, ICCC 2024. ed. / Andrzej Kot. Institute of Electrical and Electronics Engineers Inc., 2024. (Proceedings of the 2024 25th International Carpathian Control Conference, ICCC 2024).

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Harvard

Evangelista, AD, Schettino, VB, dos Santos, MF & Mercorelli, P 2024, Comparison of Trajectory Estimation Methods Based on LIDAR and Monocular Camera in a Simulated Environment. in A Kot (ed.), Proceedings of the 2024 25th International Carpathian Control Conference, ICCC 2024. Proceedings of the 2024 25th International Carpathian Control Conference, ICCC 2024, Institute of Electrical and Electronics Engineers Inc., 25th International Carpathian Control Conference - ICCC 2024, Krynica Zdroj, Poland, 22.05.24. https://doi.org/10.1109/ICCC62069.2024.10569700

APA

Evangelista, A. D., Schettino, V. B., dos Santos, M. F., & Mercorelli, P. (2024). Comparison of Trajectory Estimation Methods Based on LIDAR and Monocular Camera in a Simulated Environment. In A. Kot (Ed.), Proceedings of the 2024 25th International Carpathian Control Conference, ICCC 2024 (Proceedings of the 2024 25th International Carpathian Control Conference, ICCC 2024). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCC62069.2024.10569700

Vancouver

Evangelista AD, Schettino VB, dos Santos MF, Mercorelli P. Comparison of Trajectory Estimation Methods Based on LIDAR and Monocular Camera in a Simulated Environment. In Kot A, editor, Proceedings of the 2024 25th International Carpathian Control Conference, ICCC 2024. Institute of Electrical and Electronics Engineers Inc. 2024. (Proceedings of the 2024 25th International Carpathian Control Conference, ICCC 2024). doi: 10.1109/ICCC62069.2024.10569700

Bibtex

@inbook{cd951383b6024f1ebb8147e782cb425e,
title = "Comparison of Trajectory Estimation Methods Based on LIDAR and Monocular Camera in a Simulated Environment",
abstract = "Odometry estimation is a fundamental problem for two-dimensional locomotion in mobile robotics. When common motion sensors, such as wheel encoders, are absent or unreliable, other sensors can be employed for the same task. LIDARs are a common choice due to their precision but have relatively high cost. The monocular camera provides a cost-effective alternative but has limitations, such as reliance on lighting conditions and the absence of direct depth information. Both sensors face specific challenges when employed in indoor environments with SLAM algorithms for odometry estimation. This article proposes a comparative analysis between the Hector SLAM algorithm, based on LIDAR, and the ORB-SLAM3 algorithm, based on a monocular camera, to assess the accuracy of estimated trajectories. The sensors were mounted on a wheeled robot in a simulated environment and the simulator provided the ground truth trajectories. As expected, it was observed that the LIDAR-based algorithm performed better than the camera-based one, but the latter is an acceptable replacement for odometry estimation when the trajectories are simple and executed at lower speeds.",
keywords = "Mobile Robotics, Odometry, Visual SLAM, Engineering",
author = "Evangelista, {Amanda Dias} and Schettino, {Vin{\'i}cius Barbosa} and {dos Santos}, {Murillo Ferreira} and Paolo Mercorelli",
note = "Publisher Copyright: {\textcopyright}2024 IEEE.; 25th International Carpathian Control Conference - ICCC 2024, ICCC 2024 ; Conference date: 22-05-2024 Through 24-05-2024",
year = "2024",
month = may,
day = "22",
doi = "10.1109/ICCC62069.2024.10569700",
language = "English",
isbn = "9798350350692",
series = "Proceedings of the 2024 25th International Carpathian Control Conference, ICCC 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Andrzej Kot",
booktitle = "Proceedings of the 2024 25th International Carpathian Control Conference, ICCC 2024",
address = "United States",
url = "https://iccc.agh.edu.pl/#top",

}

RIS

TY - CHAP

T1 - Comparison of Trajectory Estimation Methods Based on LIDAR and Monocular Camera in a Simulated Environment

AU - Evangelista, Amanda Dias

AU - Schettino, Vinícius Barbosa

AU - dos Santos, Murillo Ferreira

AU - Mercorelli, Paolo

N1 - Conference code: 25

PY - 2024/5/22

Y1 - 2024/5/22

N2 - Odometry estimation is a fundamental problem for two-dimensional locomotion in mobile robotics. When common motion sensors, such as wheel encoders, are absent or unreliable, other sensors can be employed for the same task. LIDARs are a common choice due to their precision but have relatively high cost. The monocular camera provides a cost-effective alternative but has limitations, such as reliance on lighting conditions and the absence of direct depth information. Both sensors face specific challenges when employed in indoor environments with SLAM algorithms for odometry estimation. This article proposes a comparative analysis between the Hector SLAM algorithm, based on LIDAR, and the ORB-SLAM3 algorithm, based on a monocular camera, to assess the accuracy of estimated trajectories. The sensors were mounted on a wheeled robot in a simulated environment and the simulator provided the ground truth trajectories. As expected, it was observed that the LIDAR-based algorithm performed better than the camera-based one, but the latter is an acceptable replacement for odometry estimation when the trajectories are simple and executed at lower speeds.

AB - Odometry estimation is a fundamental problem for two-dimensional locomotion in mobile robotics. When common motion sensors, such as wheel encoders, are absent or unreliable, other sensors can be employed for the same task. LIDARs are a common choice due to their precision but have relatively high cost. The monocular camera provides a cost-effective alternative but has limitations, such as reliance on lighting conditions and the absence of direct depth information. Both sensors face specific challenges when employed in indoor environments with SLAM algorithms for odometry estimation. This article proposes a comparative analysis between the Hector SLAM algorithm, based on LIDAR, and the ORB-SLAM3 algorithm, based on a monocular camera, to assess the accuracy of estimated trajectories. The sensors were mounted on a wheeled robot in a simulated environment and the simulator provided the ground truth trajectories. As expected, it was observed that the LIDAR-based algorithm performed better than the camera-based one, but the latter is an acceptable replacement for odometry estimation when the trajectories are simple and executed at lower speeds.

KW - Mobile Robotics

KW - Odometry

KW - Visual SLAM

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=85198563294&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/7120e937-1800-36da-9421-996159094043/

U2 - 10.1109/ICCC62069.2024.10569700

DO - 10.1109/ICCC62069.2024.10569700

M3 - Article in conference proceedings

AN - SCOPUS:85198563294

SN - 9798350350692

T3 - Proceedings of the 2024 25th International Carpathian Control Conference, ICCC 2024

BT - Proceedings of the 2024 25th International Carpathian Control Conference, ICCC 2024

A2 - Kot, Andrzej

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 25th International Carpathian Control Conference - ICCC 2024

Y2 - 22 May 2024 through 24 May 2024

ER -

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