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MAKER: Development of Smart Mobile Robot System to Help Middle School Students Learn about Robot Perception

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Conference

2016 ASEE Annual Conference & Exposition

Location

New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

August 28, 2016

ISBN

978-0-692-68565-5

ISSN

2153-5965

Conference Session

Make It!

Tagged Division

Manufacturing

Page Count

10

DOI

10.18260/p.25617

Permanent URL

https://www.jee.org/25617

Download Count

180

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Paper Authors

biography

Sheng-Jen Hsieh Texas A&M University

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Dr. Sheng-Jen (“Tony”) Hsieh is a Professor in the Dwight Look College of Engineering at Texas A&M University. He holds a joint appointment with the Department of Engineering Technology and the Department of Mechanical Engineering. His research interests include engineering education, cognitive task analysis, automation, robotics and control, intelligent manufacturing system design, and micro/nano manufacturing. He is Director of the Rockwell Automation laboratory at Texas A&M University, a state-of-the-art facility for education and research in the areas of automation, control, and automated system integration. He also serves as Director of an NSF Research Experiences for Teachers (RET) program in the area of Mechatronics, Robotics, and Industrial Automation.

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Vania Willms

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Abstract

Mobile robots are used in many different fields, including transportation, search and rescue, demining, and space exploration. Image processing and object avoidance concepts are interesting and challenging subjects for students to learn and often come up in robotics competitions such as FIRST Robotics. The paper describes an instructional module involving the design, construction, and evaluation of a smart mobile robot system with autonomous navigation in an indoor setting for middle school students. The mobile robotic platform was built using VEX system components. The VEX ultrasonic rangefinders and an iPhone camera were positioned at different heights on the robotic platform for use in object recognition and avoidance. Real-time images were captured and uploaded to a cloud server for video streaming and object recognition. Outputs from the sensors and video streaming were used to dynamically control the movement of the mobile robot. A post-evaluation of the instructional module indicated that students highly enjoyed the hands-on experience as well as learning the subjects.

Hsieh, S., & Willms, V. (2016, June), MAKER: Development of Smart Mobile Robot System to Help Middle School Students Learn about Robot Perception Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.25617

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