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Enhancing Robotic Experiences throughout the Computing Curriculum

Published: 21 February 2018 Publication History

Abstract

The study of robotics is often an excellent recruitment motivation for students entering a computing curriculum. It is also often cited that Artificial Intelligence (AI) and related robotics is a critical area of future innovation in computing. However, there are a number of challenges to implementing a robotic curriculum at the university level. A few of those challenges include, lack of a uniform hardware platform, incongruity in the software used, and the missing significant deliverable artifacts by students at the end of a term to encourage learning and further interest. Educational robotic activities are often treated as advanced research topics with high associated costs that prohibit widespread integration into the curriculum. In this paper, we present the deployment of a multi-stage robotic platform that attempts to address these challenges and overcome the obstacles. We detail the evolution of the hardware from using a readily available LEGO Mindstorm base platform to next include the addition of an Arduino and Raspberry Pi. Likewise, we detail the transition from the basic LEGO Mindstorm software to the use of leJOS and PYTHON. At each stage, additional sensors and software libraries can likewise be added. Finally, we present an achievable academic goal for students to use the hardware and software platforms to develop a model autonomous vehicle with aspects of intelligent control, learning and adaptive behaviour. All levels of projects can be undertaken at the appropriate level of maturity for the students in the computing curriculum.

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    cover image ACM Conferences
    SIGCSE '18: Proceedings of the 49th ACM Technical Symposium on Computer Science Education
    February 2018
    1174 pages
    ISBN:9781450351034
    DOI:10.1145/3159450
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    Published: 21 February 2018

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    Author Tags

    1. ai
    2. machine learning
    3. robotics
    4. robotics in education

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    • (2024)Adding Machine-Learning Functionality to Real Equipment for Water Preservation: An Evaluation Case Study in Higher EducationSustainability10.3390/su1608326116:8(3261)Online publication date: 13-Apr-2024
    • (2023)A bibliometric analysis of the increasing knowledge base on the role of thinking teaching strategy in sciences teachingResearch in Science & Technological Education10.1080/02635143.2023.220442442:4(1086-1108)Online publication date: 20-Apr-2023
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