Fuzzy controlled color-based object sorter using robotic arm with machine vision

• Main Authors: Cruz, Levin Jaeron S., Kudhal, Jho Nathan Singh, Ligutan, Dino Dominic F., Del Rosario, Michael Carlo D.P.
• Format: text
• Language: English
• Published: Animo Repository 2016
• Subjects: Robotics; Machine theory
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/9986
• Institution: De La Salle University

Robotic arms are employed to assembly lines to increase productivity, efficiency and at the same time improve the quality of products. In this study, the main focus will be the development of a robotic arm designed for sorting of color-coded objects autonomously into desired locations as set by the user. The robotic arm is a 4-DOF M100RAK robotic arm coupled with 2_DOF gripper whose movement is controlled by the implemented fuzzy logic-based joint controller (FLJC). The machine vision system is implemented using Kinect camera and Processing software to identify the coordinates of the gripper and target objects. The machine vision system together with the MPU6050 (gyro-accelerometer) sensors provides the inputs to FLJC. The FLJC computes the required joint angles and are transmitted to Arduino microcontroller for servo control. The robotic arm's movement is tested by its accuracy of picking up target object as well as placement time the machine vision system by its accuracy of locating the gripper and target objects. The test results indicate that the success rate of picking up of objects is about 76% with a placement time on average of 50 seconds and the machine vision system is capable of determining the objects' position within 2 centimeter accuracy.