Document Type
Article
Publication Date
11-2022
Department
Department of Electrical and Computer Engineering; Department of Applied Computing
Abstract
In this paper, a mechatronics system was designed and implemented to include the subjects of artificial intelligence, control algorithms, robot servo motor control, and human-machine interface (HMI). The goal was to create an inexpensive, multi-functional robotics lab kit to promote students’ interest in STEM fields including computing and mechtronics. Industrial robotic systems have become vastly popular in manufacturing and other industries, and the demand for individuals with related skills is rapidly increasing. Robots can complete jobs that are dangerous, dull, or dirty for humans to perform. Recently, more and more collaborative robotic systems have been developed and implemented in the industry. Collaborative robots utilize artificial intelligence to become aware of and capable of interacting with a human operator in progressively natural ways. The work created a computer vision-based collaborative robotic system that can be controlled via several different methods including a touch screen HMI, hand gestures, and hard coding via the microcontroller integrated development environment (IDE). The flexibility provided in the framework resulted in an educational lab kit with varying levels of difficulty across several topics such as C and Python programming, machine learning, HMI design, and robotics. The hardware being used in this project includes a Raspberry Pi 4, an Arduino Due, a Braccio Robotics Kit, a Raspberry Pi 4 compatible vision module, and a 5-inch touchscreen display. We anticipate this education lab kit will improve the effectiveness of student learning in the field of mechatronics.
Publication Title
Conference for Industry and Education Collaboration 2022
Recommended Citation
A. Reyes, S. Reinhardt, T. Wise, N. Rawashdeh, S. Paheding, "Gesture Controlled Collaborative Robot Arm and Lab Kit", 2022 American Society for Engineering Education (ASEE) Conference for Industry and Education Collaboration (CIEC), Tempe, AZ Feb. 4-11 2022, ASEE. Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/16520
Version
Postprint
Included in
Computer Engineering Commons, Computer Sciences Commons, Electrical and Computer Engineering Commons
Publisher's Statement
This paper was submitted to the ASEE Conference for Industry and Education Collaboration (CIEC), Tempe, AZ Feb. 4-11 2022. ©2022 American Society for Engineering Education.