JRM Vol.31 No.3 pp. 405-411
doi: 10.20965/jrm.2019.p0405


Motivation System for Students to Learn Control Engineering and Image Processing

Sam Ann Rahok*, Hirohisa Oneda**, Shigeji Osawa**, and Koichi Ozaki***

*National Institute of Technology, Oyama College
771 Nakakuki, Oyama, Tochigi 323-0806, Japan

**National Institute of Technology, Yuge College
1000 Yuge, Kamijima, Ehime 794-2593, Japan

***Utsunomiya University
712 Yoto, Utsunomiya, Tochigi 321-8585, Japan

December 19, 2018
April 2, 2019
June 20, 2019
control engineering, image processing, motivation system, ARCS model

Our aim was to motivate students to study control engineering and image processing. To this end, we designed a motivation system based on the ARCS model, developed by John M. Keller, to motivate learners. We used a drone as the control object. The ARCS model consists of four steps: attention, relevance, confidence, and satisfaction. The control process is performed by capturing images from the drone’s camera on a PC via Wi-Fi, and detecting a target color using an image processing technique. Then, the PC sends the control inputs from a PID controller back to the drone to track the target color by keeping it at the center of the images. With this system, students can gain knowledge on control engineering and image processing by tuning the parameters of PID controller and image processing, and observing the responses of the drone. To assess the effectiveness of our system, we requested 150 first-grade technical college students, who had no prior knowledge of control engineering and image processing, to attend our lecture. After the lecture, the students were asked to answer a questionnaire on their interests. The result demonstrated that over 80% of them expressed an interest in learning these two techniques.

Bodily sensations of the drone responses

Bodily sensations of the drone responses

Cite this article as:
S. Rahok, H. Oneda, S. Osawa, and K. Ozaki, “Motivation System for Students to Learn Control Engineering and Image Processing,” J. Robot. Mechatron., Vol.31 No.3, pp. 405-411, 2019.
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Last updated on Jul. 19, 2024