Your PhD topic is „Passivity-Based Force/Motion Planning and Control for Tactile Manipulation“. Can you explain your topic briefly in two or three sentences?

My thesis presents a scalable, modular control framework grounded in fundamental physics. By jointly considering force and motion—the key dual variables in physical interactions—we can model manipulation tasks as interconnected, energy-based modules. This perspective opens up new avenues for planning, learning, and control methods that are both robust and inherently energy-aware.

What did you find out if you compare your work with other research approaches? What is your USP?

This framework yields minimalistic yet versatile solutions for various manipulation tasks, making control, planning, and learning significantly more efficient. It sidesteps the pitfalls of purely model-based approaches, which often compartmentalize problems and data-driven methods that rely on excessive parameters.

How can you use these results in practice?

My work spans multiple interdisciplinary areas, but two patented and commercialized technologies stand out. The first is a robust controller for contact-rich manipulation, now a standard feature in Franka robots. The second is a clinically validated, globally used adaptive robot-aided rehabilitation solution.

Committee members of the dissertation: Prof. Sami Haddadin, Prof. Neville Hogan, MIT; Prof. Oussama Khatib, Stanford 

Text: Andreas Schmitz