Authors:
Ricardo Santos
;
Mateus Silva
and
Ricardo Oliveira
Affiliation:
Departmento de Computação - DECOM, Universidade Federal de Ouro Preto - UFOP, Ouro Preto, Brazil
Keyword(s):
Odometry, Mobile Robots, Odometry Database, Odometry Calibration.
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.
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