M21 - Introducing Soft Robotics into Engineering Education: A McKibben-Muscle-Powered Jaw Module for Multidisciplinary Learning

Introduction: : Soft Robotics is an emerging subfield of robotics employing compliant, deformable materials to create systems with high flexibility and adaptability [1]. These technologies, which are often bio-inspired and with simple control logics, present a valuable opportunity to broaden robotics education by lowering the entry barrier of required knowledge of control engineering, and more importantly, offer intuitive, hands-on learning experiences for students from multiple engineering disciplines [2]. However, their integration into higher education remains largely limited due to lack of instructional resources. This abstract demonstrates the methods and results of an implemented soft robotics module originally conceived as a result of a capstone design initiative, where undergraduate students develop soft robotic educational modules. During Spring 2025, the module, titled Jaws, was selected to be implemented into three sections of a multidisciplinary sophomore engineering course with biomedical engineering inspired projects, engaging 56 total students. The module featured Pneumatic Artificial Muscles (McKibben Muscles) used to actuate a wooden jaw structure, simulating a contraction created by biological muscles. Students were tasked with optimizing the jaw design for force output by testing various actuator configurations and conducting torque analyses. In addition to technical work, students practiced professional communication by delivering structured, data-supported presentations to justify their design decisions. The module aimed to foster interdisciplinary learning in biomechanics, mechanical testing, and experimental design, while also encouraging iterative problem solving that mirror real-world engineering workflows. This project demonstrates how soft robotics can be leveraged in undergraduate curricula to enhance both technical and communication skills.

Materials and

Methods: : Over a six-week period, students worked in teams of four to design, fabricate, and test McKibben Muscles within a mechanical jaw system. Prior to the module, we shared foundational information on soft robotics, including key classifications based on materials and actuation methods. The project was implemented in three phases (1) McKibben Muscle Overview, (2) Torque Analysis and Data Collection, and (3) Final Presentation. Students constructed McKibben muscles using standardized procedures [3], silicone tubing, and manual syringes for pneumatic actuation. These actuators were integrated into a wooden jaw mechanism (Figure 1) and later into alternative anatomical models (human, cat, dolphin) (Figure 2) for comparative analysis.

Experimental testing involved varying muscle orientation to measure force output using a load cell and Arduino IDE software. Students compared experimental data to torque predictions from static analysis. Evaluation methods included two individual reflections analyzing actuator behavior, performance variability, data interpretation, and discrepancies between theoretical and measured results. The module concluded with a 10-15 minute team presentation proposing a redesigned jaw, evolving it either on its own or in combination with another animal, adapting it to improve torque output. Presentations included anatomical comparisons, proposed muscle placements and torque estimates, pitched within a sci-fi or educational museum context. Students completed a post-module survey evaluating the module’s effectiveness. The survey collected feedback on content relevance, hands-on engagement, overall satisfaction, and areas for improvement.

Results, Conclusions, and Discussions:: Forty-one participants completed the survey. Students perceived a broad range of concepts, with the top three reported being Soft Materials and Robotics (n=34) and Fabrication Methods (n=18). We asked students to rate their familiarity with soft robotics before and after on a scale from 1.0-5.0, where we saw an increase from 2.6 to 4.0. Since the course was multidisciplinary, we asked students if the module helped them integrate disciplinary knowledge, and the average response was a 3.8/5.0, landing on the ‘Agree’ side of our scale. Three other scale questions (1.0 Strongly Disagree - 5.0 Strongly Agree) had students rate how well hands-on elements supported their learning, with all averages between 3.9 and 4.2. Students reported their comfort working on new soft robotics projects, with ‘soft’ and ‘robotics’ concepts and their satisfaction with the learning outcomes, all of which had average responses above 3.5. We asked students what felt most relevant to their future career goals and the most frequent responses were Soft Robotics, Mechanical Topics, and Robotics generally. Based on those who identified their major in the response, this project resonated most with biomedical and mechanical engineering students.

While many students seemed pleased with their experience, a few expressed frustration, pointing out areas for clarity on expectations and connections across concepts. Furthermore, while the prototypes are simplistic in assembly, the module requires significant preparation from the instructor, including laser cutting and 3D printing. In future iterations, we aim to address the pain points raised by students and lower the preparation needed to implement this module. While students performed well in their final presentations, we did not collect study data on their experiences with presentations in our survey since it is a generalized survey for all of the modules we are implementing. Given the context of our course in particular, it would be useful to collect those data in future iterations.

In closing, our survey indicated that the project offers a physically straightforward prototype applying technical skills relevant for sophomore level engineering students, particularly biomedical or mechanical engineering.

Acknowledgements and/or References (Optional):: Acknowledgements
This material is based upon work partially supported by the National Science Foundation under Grant No. 2235647. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

References
[1] Yasa, O., Toshimitsu, Y., Michelis, M. Y., Jones, L. S., Filippi, M., Buchner, T., & Katzschmann, R. K. (2022). An overview of soft robotics. Annual Review of Control Robotics and Autonomous Systems, 6(1), 1–29. https://doi.org/10.1146/annurev-control-062322-100607
[2] I. U. Cayetano-Jiménez, E. A. Martinez-Ríos, R. Bustamante-Bello, R. A. Ramírez-Mendoza and M. S. Ramírez-Montoya, "Experimenting With Soft Robotics in Education: A Systematic Literature Review From 2006 to 2022," in IEEE Transactions on Learning Technologies, vol. 17, pp. 1249-1266, 2024, doi: 10.1109/TLT.2024.3372894.
[3] Midiri, J. R., Trieu, K., Xue, W., Trkov, M., Jamison, C. S. E., & Bakrania, S. (2024, June). BYOE: McKibben Creature-A Low-Cost Robotic Simulation of A Biological Environment. In 2024 ASEE Annual Conference & Exposition.