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Autonomous Navigation via Visual Servoing with a Hybrid Sensor System

Jie Liang Choo, Nur Syazreen Ahmad, and Patrick Goh
School of Electrical & Electronic Engineering, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang, Malaysia

Abstract— In this work, a framework for a hybrid sensor system is proposed to improve the visual servoing technique of an autonomous wheeled mobile robot. The system consists of an image sensor which is mounted on the robot’s robotized head and a range sensor which is fixed at the front position of the robot. The image sensor has the capability to extract the features from a 2D image but is bound to lose its detection when the distance between the sensor and the target image is too close. The range sensor, on the other hand, has the limitation of unstable detection when the target object is too far or/and not in the line of sight, but is useful when the target object is sufficiently close. Two mini nonholonomic robots are used as the test beds and a set of experiments is designed in this work to investigate the impacts of the hybrid sensor system on the tracking performance of the robot. With the speed of the robots constrained within ±20 cm/s, and the distance between them not more than 40cm, it is shown that both sensors compensate each other’s limitations in order to ensure the tracking performance is within the design requirement.

Index Terms—visual servoing, autonomous, hybrid sensor

Cite: Jie Liang Choo, Nur Syazreen Ahmad, and Patrick Goh, "Autonomous Navigation via Visual Servoing with a Hybrid Sensor System," International Journal of Mechanical Engineering and Robotics Research, Vol. 9, No. 6, pp. 906-910, June 2020. DOI: 10.18178/ijmerr.9.6.906-910

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.