Document Type

Conference Paper

Publication Date

2022

Publication Title

IAJC 2022 International Conference

Pages

031-M-22 (12 pp.)

Conference Name

IAJC 2022 International Conference, 13-16 October 2022, Orlando, Florida

Abstract

The main objective of this paper is to describe a teaching tool that can be used for automated creation of different problems that can be used for assessing student knowledge while teaching industrial robotics courses. These materials can be used for instructors who need to create customized questions and answers for different student homework. Wayne State University, Detroit, MI offer different industrial robotics and courses related to fundamental robotic theory: kinematics, dynamics, and control. Old Dominion University, Norfolk, VA offers the course in Introduction to Industrial Robotics. Both programs are Mechanical Engineering Technology under the Engineering Technology departments / division. Preparing questions for assignments, labs and projects can take enormous amount of time because of the equation’s complexity. In order to avoid repetition of same questions especially project problems, the reconfigurable kinematic and dynamic modules are used. This is especially important due to the problems that many instructors are facing due to the online systems that encourage student subscriptions and possible cheating through previously given homework and available solutions from previous exams. The developed model that will be presented in this paper is a reconfigurable module for automatic Jacobian generation that has been developed and validated at Mid-sized University A. Maple tool is used for symbolic equations and clear visibility of results. The methodology is presented in detail. Several examples are used to demonstrate the model’s capability and reusability. The reconfigurable modules are currently used for two robotic curses: Course A and Course B. It will also be expanded to University B and validated there.

Rights

© 2022 International Association of Journal and Conferences. All rights reserved.

Included with the kind written permission of the copyright holder.

Original Publication Citation

Djuric, A., & Jovanovic, V. (2022). Reconfigurable modules for automatic creating robotic courses [Paper presentation]. IAJC 2022 International Conference, Orlando, Florida.

ORCID

0000-0002-8626-903X (Jovanovic)

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