Home
The laboratory for Surgical Planning and Robotic Cognition (SPARC) at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), led by Prof. Dr. Franziska Mathis-Ullrich, investigates cognition guided robots for surgical assistance in minimally invasive procedures, intelligent and flexible surgical instruments, and intuitive interfaces between humans and robots in the operating room.
The SPARC laboratory conducts interdisciplinary research in close collaboration with national and international partners. We aim to contribute to building a healthcare system that enables optimal and personalized treatment of patients through targeted interactions between surgical experts and the next generation of minimally invasive surgical robots and assistance systems.
We are thrilled to announce that our Postdoctoral Researcher Dr.-Ing. Ramy Zeineldin has received the Best Dissertation 2023/2024 award for his PhD thesis titled "Deep Multimodality Image-Guided System for Assisting Neurosurgery" from the faculty of informatics, Karlsruhe Institute of Technology (KI...
We have a new doctor!
Congratulations to Dr.-Ing. Christian Marzi who successfully defended his doctoral thesis on "Capacitive Spatial Exteroception in Minimally Invasive Continuum Robots" as a collaborative work between KIT and SPARC at FAU Erlangen-Nürnberg.
The examination committee consist...
SPARC member Dr.-Ing. Paul Maria Scheikl gave a talk and a practical lab session on reinforcement learning in robot-assisted surgery at the summer school on control of surgical robots (COSUR) in Verona, Italy. The COSUR summer school is held every two years and targets PhD students interested to the...
On June 6th 2024, SPARC member Paul Maria Scheikl successfully defended his doctoral thesis on "Learning Visuomotor Policies for Cooperative Robot-Assisted Surgery" with the overall grade “with distinction”.
The examination committee included Prof. Franziska Mathis-Ullrich (FAU), Prof. Axel Krieg...
We are thrilled to announce that our recent paper "Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects" has been published in the IEEE Robotics and Automation Letters (RA-L).
Movement Primitive Diffusion (MPD) combines the versatility of diffusion-based imitatio...
