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

Dino Dominic Ligutan, Levin Jaeron S. Cruz, Michael Carlo D. P. Del Rosario, Jho Nathan Singh Kudhal, Alexander C. Abad, Elmer P. Dadios

Year
2017
Citations
19

Abstract

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.

Keywords

Computer scienceFuzzy logicJoint (building)RobotController (irrigation)Robotic armArtificial intelligenceControl engineeringFuzzy control systemControl theory (sociology)

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