2026 ASEE Annual Conference & Exposition

Design of a Smart Sorting Cobot Cell as an Experiential Learning Tool in Robotics and Mechatronics

Presented at Manufacturing Division (MFG) Technical Session 6

This paper presents the design, construction, and programming of a smart collaborative robot (cobot) cell as an experiential learning tool in robotics and mechatronics coursework. The senior design project embraces this trend by developing a pick-and-sort system that integrates smart cameras with a robotic arm. The goal is to provide engineering and technology students with a hands-on learning platform that combines intelligent vision capabilities with robotic control. The system supports robotics and mechatronics coursework, offering students practical experience with modern automation technologies. Key components include the IFM machine vision 2-D camera, 3-D camera, and the UFactory Lite 6 robotic arm. The 2-D camera identifies object types based on shape and size, while the 3-D camera determines object coordinates in 3D space. The robot uses this data to pick and sort objects into designated pallet zones. An additional component includes a model conveyor belt for object transport. The entire system is integrated using Python. The 2-D camera communicates via TCP/IP, the 3-D camera interfaces through the ifm3dpy API, and the robotic arm is controlled using the xArm SDK. This project delivers a fully functional smart sorting system, providing students with a valuable opportunity to explore and analyze the integration of smart technology, machine vision, and robotics in an applied setting.

Authors

Dr. Richard Y Chiou Drexel University [biography]

Dr. Richard Y. Chiou is a Professor within the Department of Engineering, Leadership, and Society at Drexel University, Philadelphia, USA. His educational background is in manufacturing with an emphasis on mechatronics. In addition to his years of industrial experience, he has taught many different engineering and technology courses at undergraduate and graduate levels. His tremendous research experience in manufacturing includes intelligent manufacturing, eco-manufacturing, Internet based robotics, and clean energy and energy efficiency. He has conducted many experimental studies on virtual reality robotics, ultrasonic robotic welding, Internet-of-Things (IoT) in intelligent manufacturing. He has also developed augmented reality/virtual reality (AR/VR) robotics and clean energy and energy efficiency laboratory recently. He has secured many research and education grants from the National Science Foundation, the US Department of Education, the Society of Manufacturing Engineers Education Foundation, and industries. Techniques developed from his research projects have been extended to the educational activities involving intelligent manufacturing with clean energy and energy efficiency.
Prof. Tzu-liang Bill Tseng http://orcid.org/0000-0002-3903-529X University of Texas at El Paso [biography]

Dr. Bill Tseng is a Professor and Chair of Department of Industrial, Manufacturing and Systems Engineering at the UTEP. He is also a Director of Research Institute for Manufacturing & Engineering Systems, the host institute of Texas Manufacturing Assistan
Dr. Yalcin Ertekin Drexel University, College of Engineering [biography]

Dr. Yalcin M. Ertekin is a Clinical Professor and Associate Program Director for Undergraduate Studies in the Engineering Technology program at Drexel University. He brings over 25 years of academic and industry experience in manufacturing, quality engineering, and engineering education. Dr. Ertekin holds a Ph.D. in Mechanical Engineering from the University of Missouri-Rolla and is a Certified Quality Engineer (CQE) and Certified Manufacturing Engineer (CMfgE). His expertise includes manufacturing processes, CNC machining, metrology, and smart manufacturing, with a strong focus on project-based learning and interdisciplinary senior design. He has served in leadership roles within the American Society for Engineering Education (ASEE), including Division Chair of the Manufacturing Division, and is actively involved in ABET accreditation as a Program Evaluator and ETAC Commissioner. Dr. Ertekin has led multiple NSF and industry-funded projects and has authored numerous peer-reviewed publications in engineering education and manufacturing.
Dr. Md Fashiar Rahman http://orcid.org/0000-0002-0437-2587 University of Texas at El Paso [biography]

Dr. Md Fashiar Rahman is an Assistant Professor of the Industrial, Manufacturing and Systems Engineering (IMSE) Department at The University of Texas at El Paso. He holds a Ph.D. degree in Computational Science Program. He has years of research experience in different projects in the field of image data mining, machine learning, deep learning, and computer simulation for industrial and healthcare applications. In addition, Dr. Rahman has taught various engineering courses in industrial and manufacturing engineering. His research area covers advanced quality technology, AI application in smart manufacturing, health care applications, computational intelligence/data analytics, and decision support systems.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026

« View session