A Computer Vision-Based Method for Collecting Ground Truth for Mobile Robot Odometry

Ricardo Santos, Mateus Silva, Ricardo Oliveira

2024

Abstract

With the advancement of artificial intelligence and embedded hardware development, the utilization of various autonomous navigation methods for mobile robots has become increasingly feasible. Consequently, the need for robust validation methodologies for these locomotion methods has arisen. This paper presents a novel ground truth positioning collection method relying on computer vision. In this method, a camera is positioned overhead to detect the robot’s position through a computer vision technique. The image used to retrieve the positioning ground truth is collected synchronously with data from other sensors. By considering the camera-derived position as the ground truth, a comparative analysis can be conducted to develop, analyze, and test different robot odometry methods. In addition to proposing the ground truth collection methodology in this article, we also compare using a DNN to perform odometry using data from different sensors as input. The results demonstrate the efficacy of our ground truth collection method in assessing and comparing different odometry methods for mobile robots. This research contributes to the field of mobile robotics by offering a reliable and versatile approach to assess and compare odometry techniques, which is crucial for developing and deploying autonomous robotic systems.

Paper Citation

in Harvard Style

Santos R., Silva M. and Oliveira R. (2024). A Computer Vision-Based Method for Collecting Ground Truth for Mobile Robot Odometry. In Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-692-7, SciTePress, pages 116-127. DOI: 10.5220/0012622900003690

in Bibtex Style

@conference{iceis24,
author={Ricardo Santos and Mateus Silva and Ricardo Oliveira},
title={A Computer Vision-Based Method for Collecting Ground Truth for Mobile Robot Odometry},
booktitle={Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2024},
pages={116-127},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012622900003690},
isbn={978-989-758-692-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - A Computer Vision-Based Method for Collecting Ground Truth for Mobile Robot Odometry
SN - 978-989-758-692-7
AU - Santos R.
AU - Silva M.
AU - Oliveira R.
PY - 2024
SP - 116
EP - 127
DO - 10.5220/0012622900003690
PB - SciTePress