M.W. (Maximilian) Stölzle

M.W. (Maximilian) Stölzle

Profile

Research

My research interest include investigating novel hybrid approaches to combine model-based and data-driven methods for the dynamic control of soft robots. I see in particular more potential in modelling the actuation dynamics. Additionally, I like to investigate how we can achieve proprioception for soft robots.

Biography

Maximilian obtained both his bachelor and master degrees in Mechanical Engineering from ETH Zürich in Switzerland. During his masters, he focused on Robotics, Systems and Control and spent a semester as an exchange student at University College London. Maximilian contributed to several research projects during his masters with one paper accepted on the topic of using neural networks for cost estimation during RRT* path planning to ICRA 2021. He worked on his master thesis in a joint research project with the Planetary Robotics Lab of the European Space Agency in the Netherlands on the topic of solving occlusion in local robot elevation maps using neural networks.  As an extracurricular activity, he served as a lead of the simulations and control team consisting of six students of the project Euler of the Academic Space Initiative Switzerland (ARIS) participating in the European Rocketry Challenge 2020 in Portugal.

In March 2021, Maximilian started his PhD on the topic of  Model-based and Data-driven Nonlinear Control of Soft Robots under guidance and supervision of Dr. Cosimo Della Santina and Prof. Babuska at the Cognitive Robotics department.

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Publications

Prizes

  • 2024-4-16

    IEEE RAS RoboSoft 2024 Best Paper Award

    Received the Best Paper Award the 2024 IEEE 7th
    International Conference on Soft Robotics (RoboSoft) for the work on Guiding soft robots with motor-imagery brain signals and impedance contro
    7th IEEE International Conference on Soft Robotics, RoboSoft 2024

Ancillary activities