Design and implementation of a fuzzy logic-based joint controller on a 6-DOF robot arm with machine vision feedback

• Main Authors: Ligutan, Dino Dominic F., Cruz, Levin Jaeron S., Del Rosario, Michael Carlo D.P., Kudhal, Jho Nathan Singh, Abad, Alexander C., Dadios, Elmer Jose P.
• Format: text
• Published: Animo Repository 2018
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/817; https://animorepository.dlsu.edu.ph/context/faculty_research/article/1816/type/native/viewcontent
• Institution: De La Salle University

© 2017 IEEE. This study presents the design, simulation and implementation of a fuzzy logic-based joint controller (FLJC) on a six-degrees of freedom (6-DOF) robotic arm with machine vision feedback capable of picking an object and placing it to a predetermined position. A 4-DOF M100RAK robotic arm coupled with 2-DOF gripper is used as a platform in the implementation of the FLJC. The control of robotic arm system is a closed-loop system. The inputs to the FLJC are the joint angles, gripper coordinates and target object coordinates. Input joint angles are measured using MPU6050 Six-Axis (Gyro+Accelerometer) sensor. Machine vision system composed of Kinect camera and an opensource Processing software are used to extract the coordinates of the gripper and the target within the image of the workspace. Computed joint angles from FLJC are transmitted through communication protocol packets to Arduino microcontroller for servo control.