Abstract
A demonstration of the application of fuzzy logic-based joint controller (FLJC) to a 6-DOF robotic arm as a color-based sorter system is presented in this study. The robotic arm with FLJC is integrated with a machine vision system that can discriminate different colors. Additionally, the machine vision system composed of Kinect camera and computer were used to extract the coordinates of the gripper and the objects within the image of the workspace. A graphical user interface with an underlying sorting algorithm allows the user to control the sorting process. Once the system is configured, the computed joint angles by FLJC are transmitted serially to the microcontroller. The results show that the absolute error of the gripper coordinates is less than 2 cm and that the machine vision is capable of achieving at least 95% accuracy in proper color discrimination both for first and second level stacked color objects.
Highlights
The development of machines has been a valuable tool ever since the dawn of civilization
One such controller developed in this study is the fuzzy logic-based joint controller (FLJC) [4] that is capable of dealing with system nonlinearities by moving the joints of the robotic arm at proper rate and interval according to the task at hand
The color-based sorter system is similar to the configuration in [4] but with the following modifications: 1) the robotic arm’s end-effector are embedded with limit switches to improve tactile sensing of the object, 2) the machine vision system is capable of discriminating at most four different object colors, and 3) the sorter is capable of sorting out stacked objects up to second level
Summary
The development of machines has been a valuable tool ever since the dawn of civilization. Non-classical or intelligent controllers had been developed throughout the years, such as fuzzy logic based controllers [5], [6] that mimics the way humans think, artificial neural network based controllers [7], [8] that emulates the biological human brain, genetic algorithm based controllers [9], [10] inspired by evolutionary processes or hybrid types [11] One such controller developed in this study is the fuzzy logic-based joint controller (FLJC) [4] that is capable of dealing with system nonlinearities by moving the joints of the robotic arm at proper rate and interval according to the task at hand. Several points are enumerated with regards to the possible improvements that could be made for the system
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