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| Funder | European Commission |
|---|---|
| Recipient Organization | Katholieke Universiteit Leuven |
| Country | Belgium |
| Start Date | Jan 01, 2021 |
| End Date | Jun 30, 2024 |
| Duration | 1,276 days |
| Number of Grantees | 6 |
| Roles | Participant; Third Party; Coordinator |
| Data Source | European Commission |
| Grant ID | 101016985 |
FAROS aims at improving functional accuracy through embedding physical intelligence in surgical robotics. A key motivation for introducing robots in operating rooms has been their ability to deliver superhuman performance.
However, for the vast majority of surgical procedures, robotic positioning precision alone is not sufficient to realize the right gesture.
Indeed, surgical accuracy is a different concept from standard engineering notions such as geometric precision, resolution or sensitivity.
This arises from the essence of the surgical tasks: surgeons do not let their gestures be dictated by pure geometric objectives; rather, functional objectives are what they pursue. FAROS explores venues to efficiently embody surgeon-like autonomous behaviour at different levels of granularity.
The following key ingredients are foreseen: (1) a rich set of non-visual sensors that form a multifaceted representation of the surgical task; (2) functional models that relate non-conventional sensor signals to functional parameters (e.g. tissue type, quality of tissue or bone, condition of tissue/fluid, tissue damage, perfusion, implant stability, etc.); and (3) functional controllers, obtained through reinforcement learning, that encode physical intelligence and produce sensible autonomous robot actions geared at closing knowledge gaps or optimizing functional performance.
This new concept, which we refer to as Functionally Accurate RObotic Surgery (FAROS), will be showcased on two critical spine surgery use cases, namely: pedicle screw placement and endoscopic lumbar discectomy.
A compact yet multi-disciplinary team consisting of academics, industry and end-users will collaborate closely to build up robotic controllers that are better suited at delivering functional accuracy in the presence of large variability and disturbances inherent to every surgical act.
Universitat Zurich; Centre National de la Recherche Scientifique CNRS; Katholieke Universiteit Leuven; Spineguard; King's College London; Sorbonne Universite
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