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Multi-Sensors for Robot Teaming Using Raspberry Pi and VEX Robotics Construction Kit

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2018 ASEE Annual Conference & Exposition


Salt Lake City, Utah

Publication Date

June 23, 2018

Start Date

June 23, 2018

End Date

July 27, 2018

Conference Session

Automation in Manufacturing

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Paper Authors


Shouling He Vaughn College of Aeronautics & Technology

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Dr. Shouling He is an associate professor of Engineering and Technology at Vaughn College of Aeronautics and Technology, where she is teaching the courses in Mechatronics Engineering and Electrical Engineering Technology. Her research interests include modeling and simulation, microprocessors and PLCs, control system designs and Robotics. She has published more than 45 journal and conference papers in these research areas.

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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 also the 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.

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The paper presents an engineering design approach to develop an instructional module for college students to learn Microprocessors and Robotics using multiple sensors, microprocessors and software design tools. The module consists of research analysis, lesson content development and laboratory practice selection, which satisfies the ABET (Accreditation Board for Engineering & Technology) requirement for engineering education. The research analysis covers the work reported by the scholars from MIT and other universities, where the main concern is how to enhance students’ capability in developing autonomous robots using new technologies in the industry, such as multiple sensor fusion methodology as well as working skills on cross-platform hardware (Intel, ARM, AMD and PIC, etc) and software (Linux, Windows and Androids, etc) systems. After the research paper analysis, a class activity has been developed. The activity includes teaching students to build teaming robots using the Cortex controllers programmed under Windows and the Raspberry Pi (in ARM cores) under Linux-like system with Pi Camera. The robot teaming under investigation contains two robots. The first robot equipped with an ultrasonic sensor in the front can turn in any direction. When it “sees” an obstacle ahead, it will turn left or right to avoid the obstacle. The second robot has a Cortex controller to drive the motors and an ultrasonic range finder to detect the distance between it and the front robot. At the same time, the second robot also holds a Raspberry Pi board with a Pi Camera on it. The image signal obtained from the Pi Camera is processed by the Raspberry Pi board and sent to the Cortex controller. Based on the processed image signal, the second robot can see the first robot turn left or right and follow it to turn, thus, they make a robot team. In the engineering design and implementation process, students will learn how to develop, program and test the two robots, particularly the second robot, as well as how to evaluate the result through the cross-platform systems.

He, S., & Hsieh, S. (2018, June), Multi-Sensors for Robot Teaming Using Raspberry Pi and VEX Robotics Construction Kit Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. 10.18260/1-2--30829

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