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From equations to actions: A system level design research experience of an undergraduate student

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Conference

ASEE Southeast Section Conference

Location

Arlington, Virginia

Publication Date

March 12, 2023

Start Date

March 12, 2023

End Date

March 14, 2023

Conference Session

Using Research in Engineering Ed

Tagged Topic

Professional Engineering Education Papers

Page Count

15

DOI

10.18260/1-2--45012

Permanent URL

https://peer.asee.org/45012

Download Count

168

Paper Authors

biography

Vincenzo Alessandro Macri Florida Atlantic University

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I am an undergraduate student at Florida Atlantic University pursuing a double major in Computer Science and Computer Engineering with a focus on Machine Learning. I have been a part of the Machine Perception and Cognitive Robotics Lab (MPCR Lab) on campus where I have had experience building Deep Neural Networks, Convolutional Neural Networks, and Reinforcement Learning agents for a range of different tasks, since the summer of 2018. Additionally, I have done research on Mixed Reality and its applications in the field of education using the Magic Leap One device. Currently, my main research focus in the lab is on creating intelligent avatars for virtual spaces. Aside from the lab where I enjoy spending the majority of my time, I am also a shift manager at Red Button Escape, a Web Assistant for FAU where I maintain the website for the Department of Electrical Engineering and Computer Science (EECS), and a paid Research Assistant. Outside of my work and academic life, I have a strong passion for the performing arts and music. In my free time, I enjoy coding, playing piano, singing, biking, and traveling.

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biography

Daniel Raviv Florida Atlantic University

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Dr. Raviv is a Professor of Computer & Electrical Engineering and Computer Science at Florida Atlantic University. In December 2009 he was named Assistant Provost for Innovation and Entrepreneurship.

With more than 30 years of combined experience in the high-tech industry, government and academia Dr. Raviv developed fundamentally different approaches to “out-of-the-box” thinking and a breakthrough methodology known as “Eight Keys to Innovation.” He has been sharing his contributions with professionals in businesses, academia and institutes nationally and internationally. He was a visiting professor at the University of Maryland (at Mtech, Maryland Technology Enterprise Institute) and at Johns Hopkins University (at the Center for Leadership Education) where he researched and delivered processes for creative & innovative problem solving.

For his unique contributions he received the prestigious Distinguished Teacher of the Year Award, the Faculty Talon Award, the University Researcher of the Year AEA Abacus Award, and the President’s Leadership Award. Dr. Raviv has published in the areas of vision-based driver-less cars, innovative thinking, and teaching innovatively. He is a co-holder of a Guinness World Record. He is a co-author of five books on innovative thinking and teaching innovatively.

Dr. Daniel Raviv received his Ph.D. degree from Case Western Reserve University in 1987 and M.Sc. and B.Sc. degrees from the Technion, Israel Institute of Technology in 1982 and 1980, respectively.

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Juan David Yepes Florida Atlantic University

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Abstract

With the trend of autonomous vehicles and world sensing devices becoming more widespread, the importance of learning computer vision is becoming clearer. In the standard academic environment, the average undergraduate student is deprived of the opportunity to engage in research and experience real world problem solving specifically on a hands-on, system level within the computer vision space. This paper outlines the learning journey of an undergraduate student studying the basics and practical applications of a novel computer vision algorithm called visual looming, highlighting the challenges faced along the way and the ways those challenges were overcome. In this paper we share the learning approach, skills acquired, and knowledge gained.

Entering this study with no prior knowledge of visual looming and only basic computer vision knowledge, the student was given the opportunity to discover unique and creative approaches to solving the problem without the bias of past literature. Using this self-guided approach to learning, the student was able to produce several divergent solutions using differing computer vision techniques to implement the looming algorithm on an Nvidia processor located on a motorized 3-wheeled rover. Through the constant prototyping of these different solutions, the student inherently ran into many challenges on both the hardware and software level which required out-of-the-box thinking and real world problem solving skills to overcome. With the guidance of a professor and a doctoral student, each with over 25 years of computer vision experience, the student was able to learn how to use available resources to navigate through hurdles in the design process and eventually converge on a final design solution.

By the end of the process the student was able to successfully develop a system level solution to demonstrate the visual looming algorithm in practice by having the 3-wheeled rover keep a constant distance away from a moving object, using a feedback control loop to govern the rover’s movement based on calculated looming values collected using computer vision techniques. This system level project required a plethora of skills including the ability to look at the bigger picture, the understanding of hardware and software interactions, the clever use of tools like GitHub and Discord for collaboration, the ability to receive and use constructive comments to enhance the final design and all around creative, and out-of-the-box divergent thinking.

We will explore in great depth many of these skills the student learned through this experience that may be beneficial to other instructors looking to bridge the gap between the academic classroom and real-world problem solving. Altogether, this paper will shed light on the inner details of a self guided learning experience and demonstrate the benefits of creative exploration and hands-on experimentation when learning and applying a new topic.

Macri, V. A., & Raviv, D., & Yepes, J. D. (2023, March), From equations to actions: A system level design research experience of an undergraduate student Paper presented at ASEE Southeast Section Conference, Arlington, Virginia. 10.18260/1-2--45012

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