My name is Valeria Lesseur, and I am a Mechatronics student from Mexico. A year ago, I came across the call for the SPP100 Programme, which offered the opportunity to do a research internship in Germany focused on Soft Robotics. I was incredibly excited by the idea, especially because during my studies, I had the chance to work on a project related to the design of soft actuators, which fascinated me due to the potential of this technology. Without hesitation, I decided to apply.
There were several projects to choose from, all focused on different disciplines, but control is definitely the most exciting one. That’s why the project titled "Self-Sensing Estimation and Sensorless Control of Three-Dimensional DE-Driven Soft Robotic Manipulators" immediately caught my attention. After a few months, I was invited for an interview with Professor Gianluca Rizzello, the project leader, and Giovanni Soleti, who would be my mentor during the internship. In the interview, they explained the project in detail, which only increased my enthusiasm. I couldn’t stop imagining myself working with them on this project, and of course, living in Germany and exploring Europe—another exciting part of the internship.
A few months later, I received the news that I had been accepted, and my adventure began. Now, after six months of the internship, I can share what this experience has been like.
The project I’m working on focuses on developing a platform made of two dielectric elastomer actuators that work as antagonist-agonist muscles: when one contracts, the other extends, generating movement. These actuators also serve as self-sensors because they function as deformable capacitors. When the voltage increases, the actuator size also increases, causing a change in capacitance. This allows us to estimate the length of the actuator based on voltage and capacitance measurements. However, since the actuators require a voltage of 3kV, conventional capacitance meters cannot be used because they would burn out at such high voltages. Instead, we measure voltage and current, and from those measurements, we estimate the capacitance, and subsequently, the actuator’s length.
During the first few months of the internship, my focus was on achieving these estimates. I learned about parameter identification methods, such as Least Squares, and also became familiar with other methods like polynomial fitting. Additionally, I had to adapt to the challenges of working with real-time systems.
Once we completed this phase, we moved on to the main objective: estimating the platform's position. In previous work, a model-based control method was implemented to control the platform with great precision. Although it works perfectly, the situation becomes more complex when additional platforms are added, as the idea is to create a tentacle made up of several stacked T-platforms. For this reason, they decided to explore the possibility of using neural networks to estimate the platform’s position based on voltage and capacitance measurements.
So, I had to learn about neural networks from scratch—and it’s been quite a challenge! I’m still working on improving the results of my neural network, but it has been an interesting process of experimentation, result analysis, and discussions on how to improve the models. Essentially, it's been the daily routine of research.
Since I started my degree, I’ve always been drawn to research. I enjoy learning, applying my knowledge, and delving into advanced science. However, I also had the opportunity to work in industry, and I really enjoyed that experience as well. The work dynamic in industry is di@erent from research, and both worlds have their appeal. So, when the opportunity to do this internship came up, my plan was to try out research and see how I liked it. Now, after six months, I am certain that my path is in research.
I have fallen in love with my daily life as a researcher. I enjoy conversations with my colleagues about our projects, meetings to discuss progress and next steps, the freedom to explore new ideas, and most of all, the constant learning. They say that the more you learn, the more you realize how little you know, and I truly believe that. During this time, I’ve learned just how vast the fields of engineering and control are, and I am more motivated than ever to keep learning.
I love Mexico with all my heart (especially now that I’ve gone six months without tacos), but I recognize that research is not as widely promoted there, which limits opportunities for building a career in this field. That’s why I appreciate even more having had the chance to discover my passion and acquire skills and experience that will allow me to continue developing it.