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ASEE-SE Annual Conference 2022

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Bridging The Sustainable Digital Divide In Artificial Intelligence Enabled Robotics Education

Abstract – This paper will examine and demonstrate the feasibility of an efficient, sustainable, and affordable educational platform for advanced robotics concepts, which is suitable for multi-robot, human-robot interaction, and autonomy research applications. It will also explore the need for educational resource support, and detail the platform’s use in service learning projects intended to introduce advanced robotics concepts, wearable devices and applications at the undergraduate level. A brief comparison of available platforms with similar capabilities will be made in order to demonstrate how the significant economic investment required for more advanced pre-built robotics platforms capable of performing functions, such as autonomous behaviors and navigation, presents a significant obstacle. From an educational perspective, there are few sustainable and affordable platforms from which to base a curriculum needed to support the effort to bridge the digital divide, nor are there many complete informational resources available, which would allow inexperienced users to assemble, operate, and develop applications for these systems. A functional platform will be introduced, along with current efforts to develop educational resources and improve the overall capabilities, cost, and sustainability of the proposed platform.

Index Terms – Robotics Education, STEM Education, Machine Learning, SLAM, Multi-Master, Multi-Robot Autonomy, ROS, Computer Vision, wearable technology, human computer interaction, Ad-Hoc Mesh Network

Rutledge Detyens
The Citadel
United States

Andrew Gunn
Clemson University
United States

Justin Geisler
University of Alabama
United States

Ryan Integlia
The Citadel
United States

 


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