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Advancing Soft Robot Modeling: Integrating Physics, Optimization, and Control
We are advancing soft robot simulation with FEM and energy-based methods to model complex, adaptive behaviors. This research entails developing the framework to support diverse designs, integrate new physics models, and optimize performance, enabling enhanced control and real-world applications of soft robots.
Soft robots are characterized by their ability to deform continuously and adapt to complex environments, making them ideal for tasks in unstructured and dynamic settings. Our lab is developing a cutting-edge soft robot modeling framework that employs FEM and energy-based methods to simulate these robots. We are now expanding this framework to support diverse robot designs, optimize performance, and incorporate new types of physics. By contributing to this effort, you will help refine the tools needed to benchmark, optimize, and control soft robots, pushing the boundaries of what they can achieve in both research and real-world applications.
Soft robots are characterized by their ability to deform continuously and adapt to complex environments, making them ideal for tasks in unstructured and dynamic settings. Our lab is developing a cutting-edge soft robot modeling framework that employs FEM and energy-based methods to simulate these robots. We are now expanding this framework to support diverse robot designs, optimize performance, and incorporate new types of physics. By contributing to this effort, you will help refine the tools needed to benchmark, optimize, and control soft robots, pushing the boundaries of what they can achieve in both research and real-world applications.
Possible work packages are:
- Extend the existing soft robot framework for specific soft robot designs (e.g., soft manipulators or bio-inspired robots).
- Implement benchmark simulations to evaluate framework performance and accuracy.
- Introduce new physical models (e.g., fluid-structure interaction, electromagnetism, or thermal dynamics).
- Develop and improve optimization and control strategies for soft robots.
Possible work packages are:
- Extend the existing soft robot framework for specific soft robot designs (e.g., soft manipulators or bio-inspired robots). - Implement benchmark simulations to evaluate framework performance and accuracy. - Introduce new physical models (e.g., fluid-structure interaction, electromagnetism, or thermal dynamics). - Develop and improve optimization and control strategies for soft robots.
- Strong academic background with exceptional grades in physics, computer science, mechanical engineering, biomedical engineering, or related fields.
- Strong programming skills (C++ and Python).
- Proficiency in FEM-based simulations.
- Enthusiasm for interdisciplinary research and a keen interest in soft robotics.
- Capable of both working independently and cooperating with mentors and teammates.
- Strong academic background with exceptional grades in physics, computer science, mechanical engineering, biomedical engineering, or related fields. - Strong programming skills (C++ and Python). - Proficiency in FEM-based simulations. - Enthusiasm for interdisciplinary research and a keen interest in soft robotics. - Capable of both working independently and cooperating with mentors and teammates.
Manuel Mekkattu, manuel.mekkattu@srl.ethz.ch, Soft Robotics Lab, D-MAVT, ETH Zürich
Prof. Robert Katzschmann, rkk@ethz.ch, Soft Robotics Lab, D-MAVT, ETH Zürich
Earliest start: February 1, 2025
If you are interested, please submit a motivation letter, your CV, and transcripts.
Manuel Mekkattu, manuel.mekkattu@srl.ethz.ch, Soft Robotics Lab, D-MAVT, ETH Zürich
Prof. Robert Katzschmann, rkk@ethz.ch, Soft Robotics Lab, D-MAVT, ETH Zürich
Earliest start: February 1, 2025
If you are interested, please submit a motivation letter, your CV, and transcripts.
SoftRobotsModeling.pdf
