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µSAFABOT: A Robotics Learning Platform for a Hands-on, Laboratory-based Approach in an Introductory ECE Course

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2021 ASEE Virtual Annual Conference Content Access


Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Electrical and Computer Division Technical Session 4

Tagged Division

Electrical and Computer

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Paper Authors


Steven M. Beyer United States Air Force Academy

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Mr. Steven M. Beyer is an Instructor of Electrical and Computer Engineering at the United States Air Force Academy, Colorado. He recently received his Master’s in Computer Engineering (Distinguished Graduate) at the Air Force Institute of Technology, Wright-Patterson Air Force Base, Ohio. His thesis investigated vulnerabilities in commercially-available smart home devices, demonstrating how an eavesdropper can track users, identify devices, map networks, and gain unfettered access to a smart home while the user is away. He received the Chancellor’s Award in recognition of the most exceptional Master’s thesis in the Graduate School of Engineering and Management. Captain Beyer presented his findings at the 2018 NATO hosted Specialists’ Meeting on Cyber Physical Security of Defense Systems and was published in the IEEE Internet of Things Journal.

Previously, Mr. Beyer was a Test Engineer at the 46th Test Squadron, USAF (46 TS). He received the 46 TS Test Engineer of the Year award during his time as a Sensors and Defensive Systems Test Engineer, he led and conducted 15 high-profile tests for the Air Force, Army, Navy, and German Head of State, ranging from missile warning systems, radar systems, cruise missile defense systems, and flare systems. Significantly, several of these tests resulted in the systems being immediately fielded downrange. Additionally, he deployed as the AFCENT Datalinks Interoperability Officer providing training, acquisition, and engineering level support for all of CENTCOM. During this deployment he consolidated three digital networks into one providing continuous situational awareness and digital targeting for A-10s in Iraq and Syria. His efforts supporting the warfighter won him the AFMC General John P. Jumper Award for Excellence in Warfighting Integration.

After graduating college, Mr. Beyer worked for Daimler Trucks North America as the Software Design Lead for the Reliability Development Center—he led a team of engineers across the United States and Germany designing and developing an automated network based post-processing tool to visualize terabytes of engine data saving countless man hours.

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Brian James Neff United States Air Force Academy

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Col Brian J Neff is the permanent professor and department head for Electrical and Computer Engineering at the United States Air Force Academy, Colorado. He completed his PhD in Electrical Engineering at the Air Force Institute of Technology, Wright-Patterson Air Force Base, Ohio. His dissertation focused on blind deconvolution and multi-surface estimation using a 3-D flash LIDAR.

Previously, Col Neff was a squadron commander for the 746th Test Squadron at Holloway Air Force Base where he directed developmental test activities for GPS and Inertial Navigation Systems. Col Neff is a 2007 graduation of the United States Air Force Test Pilot School and continues to be adjunct faculty there, teaching Fundamentals of Electronic Warfare and Electro-Optics.

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This paper focuses on the design, implementation, and evaluation of an introductory electrical and computer engineering course that integrates theory, hands-on practice, and real-world application through the implementation of a fully customizable robotics system, µSAFABOT. This course is required for all electrical and computer engineering students, but specifically targets undeclared students at a liberal arts military academy. The previous version of the course was a traditional, lecture-based course that introduced circuits and software design. The new version of the course covers most of the same topics, but through a series of projects that culminate in a robotics maze competition. Redesign was motivated after two shortfalls were discovered: first, the number of electrical and computer engineering majors graduating each year was declining, and second, students graduating out of the major did not have necessary experience or knowledge in robotics.

Using best practices in engineering education, the course transitioned from a lecture model to a project-based learning model that includes three blocks over a forty-lesson semester: block 1, introductory topics; block 2, robotics design and implementation; and block 3, maze competition. Each laboratory includes a brief fifteen-minute introduction to a fundamental electrical and computer engineering concept and 3.5-hours of hands-on application. For example, after learning how the average power of a system can be controlled via pulse-width modulation, students integrate motors into the robot and connect each motor to a modern measurement tool to observe the digital pulse-width modulation signals sent to the robot and calculate the response time of the motors.

Evaluation measures include a pre/post survey that measure student excitement in the course, intent to major in electrical and computer engineering, and understanding of the field. Additionally, an exit survey upon graduation evaluates student intent to pursue a career in robotics. Lastly, registration data observes pre/post number of students in the major. Results show significant increases in interest in the field of electrical and computer engineering, number of majors, and student learning.

Beyer, S. M., & Neff, B. J. (2021, July), µSAFABOT: A Robotics Learning Platform for a Hands-on, Laboratory-based Approach in an Introductory ECE Course Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference.

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