Comparison of Trajectory Estimation Methods Based on LIDAR and Monocular Camera in a Simulated Environment
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Proceedings of the 2024 25th International Carpathian Control Conference, ICCC 2024. Hrsg. / Andrzej Kot. Institute of Electrical and Electronics Engineers Inc., 2024. (Proceedings of the 2024 25th International Carpathian Control Conference, ICCC 2024).
Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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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 - Publisher Copyright: ©2024 IEEE.
PY - 2024
Y1 - 2024
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
U2 - 10.1109/ICCC62069.2024.10569700
DO - 10.1109/ICCC62069.2024.10569700
M3 - Article in conference proceedings
AN - SCOPUS:85198563294
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 -