Projektbeschreibung
Neue Steuerung von Chirurgierobotern
Werden Chirurgieroboter jemals völlig eigenständig operieren können? Computergesteuerte Anlagen, die im OP zum Einsatz kommen, werden bisher direkt von chirurgisch geschulten Fachkräften bedient. Noch ist keine Autonomie des Roboters vorhanden. Moderne robotertechnische Ansätze zielen zwar auf absolute geometrische Präzision ab, doch in der Chirurgie zählt funktionelle Genauigkeit (in Relation zu den operierten anatomischen und funktionellen Strukturen). Das EU-finanzierte Projekt FAROS entwickelt jetzt neue Möglichkeiten, Chirurgieroboter mit physikalischer Intelligenz auszustatten. Dazu wird eine funktionale Repräsentation der chirurgischen Aufgabe erstellt, in der wichtige nicht visuelle Schlüsselreize erkannt werden müssen. Zusätzlich wird maschinelles Deep Learning interoperative Daten interpretieren. An Operationen der Wirbelsäule wird das Projekt demonstrieren, dass Chirurgieroboter auf diese neue Art kritische Schritte autonom ausführen können.
Ziel
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.
Wissenschaftliches Gebiet
- natural sciencescomputer and information sciencesartificial intelligencemachine learningreinforcement learning
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- medical and health sciencesclinical medicinesurgeryrobotic surgery
Schlüsselbegriffe
Programm/Programme
Aufforderung zur Vorschlagseinreichung
Andere Projekte für diesen Aufruf anzeigenUnterauftrag
H2020-ICT-2020-2
Finanzierungsplan
RIA - Research and Innovation actionKoordinator
3000 Leuven
Belgien