Professor of Mechanical Engineering and Smart Structures, School of Computing Engineering and Mathematics, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
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.
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