Real-time Vision image processing based on LabVIEW and Microcontroller controlled Parallel Robot

Manual inspections and executions in factory operations are not efficient, with many issues regarding accuracy, precision, and control. This research presents the development of camera vision to classify the different colors of the target object and works with parallel robots to pick and place objects. The efficiency of using the camera and the robot’s accuracy is studied by simulating a suitable robot workspace with MATLAB Simulink. The focus is on developing a parallel robotic arm that can be used in practice using the kinematic computational. Two key components are studied: robot kinematics for motion analysis by designing a prototype of a parallel robot that can be controlled automatically by Arduino microcontroller, and vision analysis to check and analyze the target object’s different colors by using a camera and NI vision LabVIEW. The camera vision and the robotic arm were set up together to inspect three spherical metal specimens of different colors: blue, yellow, and red. The parallel robot will pick and move the workpiece to various positions in conjunction with the vision system. The experimental result is found satisfactory and can be used effectively. The accuracy of image processing detection is 100.00%, and the kinematic of the robot actuator for picking and placing to the correct position is 100%.