Vision-based Object Tracking Experiment for Students to Perform Simple Industrial Robotic Automation

Abstract

The paper describes the details of a student vision project at XXXX University for a robot to pick up parts from the conveyor belt and place them accurately into a drop-off fixture. In an effort to generate interest within the robotic program and from local industries, the XXXXXXXXXXXXXXX University responded to strength its curriculum by adding new innovative components in its robotics and automation course, such as machine vision. A key component in the robotics and automation course is the hands-on experience where student teams use and apply the vision systems hardware and software in an automated work-cell. In addition, the students are taught the principles of vision integration with other control devices, such as robots and Programmable Logic Controllers (PLCs). The experiment results make the students understand the vast use of sensor data, combining the power of the Jevois Smart Machine Vision camera. This data can be used by any autonomous robot to reach to the object of interest or for any user to find an object location. This project was embarked as a collaborative effort between the undergraduate students and a graduate student at XXXX University. Technical issues, collaborative efforts, and student learning outcomes in the execution of this project are discussed in the paper.