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Development of Virtual Labs for Soft Robotics Courses to Enhance Student Learning and Support Faculty Teaching

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Conference

2025 ASEE Annual Conference & Exposition

Location

Montreal, Quebec, Canada

Publication Date

June 22, 2025

Start Date

June 22, 2025

End Date

August 15, 2025

Conference Session

ME Division 9: Enhancing Lab Experiences

Tagged Division

Mechanical Engineering Division (MECH)

Page Count

22

DOI

10.18260/1-2--56292

Permanent URL

https://peer.asee.org/56292

Download Count

6

Paper Authors

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Fahim Dorsey Kennesaw State University

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Connor Joseph Talley Kennesaw State University

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Razvan Cristian Voicu Kennesaw State University

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Dr. Razvan Cristian Voicu is a faculty member in the Department of Robotics and Mechatronics Engineering at Kennesaw State University. His research interests include artificial intelligence, robotics, and the development of AI-driven systems for knowledge transfer and adaptive learning. Dr. Voicu is dedicated to exploring innovative applications of AI to enhance learning and problem-solving in complex environments.

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Ayse Tekes Kennesaw State University Orcid 16x16 orcid.org/0000-0002-9537-2098

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Ayse Tekes is an Associate in the Mechanical Engineering Department at Kennesaw State University. She received her B.S., M.S. and Ph.D. in Mechanical Engineering from Istanbul Technical University, Turkey.

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Abstract

Soft robotics is an emerging field that deals with the design, modeling, and fabrication of robotic systems made of soft and compliant materials mimicking the motion in nature. Since soft robotics will revolutionize the safe interaction of humans and robots due to the application of soft materials in the robot’s structure, the next generation of robotics will yield more towards soft robotics. Engineering programs should introduce this cutting-edge technology in their curriculum that is designed to satisfy societal challenges provide a template for the advances in soft robotics, and support students to learn and explore these revolutionary changes to prepare the U.S. workforce for advanced robotics careers. However, despite the rapid growth of soft robotics, the resources available to the engineering faculty and students are very limited. Also, as the COVID-19 pandemic has forced universities to shift to emergency remote instruction, digital learning tools have become a necessity, not just an accessory, to support students’ access to resources and to facilitate their engagement and learning. To meet the needs of developing technological solutions in soft robotics courses by visualizing complex concepts, improving students’ core understanding of the material, and growing their confidence for emerging engineering careers, we developed an open-source and user-friendly virtual lab using MATLAB Simscape for soft robotics and compliant mechanisms courses to simulate and visualize the core concepts. The developed virtual lab enables students and faculty to visualize and simulate complex concepts in soft robotics, which are often challenging to grasp through traditional teaching methods. By integrating teaching methodologies with interactive simulations, our virtual lab simplifies the learning process and enriches the teaching experience. The virtual lab enables students and faculty to visualize and simulate complex concepts in soft robotics, which are often challenging to grasp through traditional teaching methods. By integrating teaching methodologies with interactive simulations, our virtual lab simplifies the learning process and enriches the teaching experience. The virtual lab includes a comprehensive library of compliant components, such as flexure hinges and flexible beams (e.g., fixed-fixed, fixed-free, and initially curved). It also features a variety of compliant mechanisms like double-dwell, bistable, parallel-arm, four-bar, and five-bar systems. Furthermore, it offers detailed comparisons between theoretical models, such as the pseudo-rigid-body model (PRBM), MATLAB Simscape simulations, Ansys results, and experimental data obtained from 3D-printed lab kits and machine vision measurements. To support active learning, the virtual lab is complemented by a set of example activities that can be used for homework or in-class demonstrations.

Dorsey, F., & Talley, C. J., & Voicu, R. C., & Tekes, A. (2025, June), Development of Virtual Labs for Soft Robotics Courses to Enhance Student Learning and Support Faculty Teaching Paper presented at 2025 ASEE Annual Conference & Exposition , Montreal, Quebec, Canada . 10.18260/1-2--56292

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