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— Ultrasonic sensor is a tool that can provide information about environmental conditions. That way, ultrasonic sensors are often used in detecting objects by measuring the distance so that they can get closer to or away from the object. Ultrasonic SRF 05 mode 2 is used in this design where the data receiver and sender lines are on one pin. Therefore, a robotic arm was designed with the ability to detect objects using ultrasonic sensors. Detection of objects not only requires results that can measure distance only. However, detection also requires accuracy in measuring and measurable in providing detection results. Artificial neural network and shear mode control are used in this study to control ultrasonic SRF 05 mode 2 to improve more accurate and measurable results in object detection. The results of this study can be concluded that the ANN method and the sliding mode control with the SRF 05 mode 2 sensor model in moving the robot arm to take the object in front of it, get a detection accuracy level with objects of 48.5 cm and the accuracy of the detection distance to objects of 50 cm. That way, the ultrasonic sensor can be more reliable and precise by using this method.
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