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Description
This book summarizes the research carried out in the context of the European project ARS (Autonomous Robotic Surgery) addressing the development of methods to add autonomous features to robotic surgery and exploring the challenges of embodied AI. This research was funded by the European Research Council Advanced Grant, ERC-ADG N. 742671 from October 1, 2017, to September 30, 2023.
There is the need of an overall, coherent picture of the research, which cannot be derived from other publications or doctoral theses. Furthermore, result dissemination and their impact have not been documented yet. These aspects are essential to give readers the complete understanding of all aspects and efforts needed to make novel technologies available for the good of people.
The main outcomes of the ARS project were the development of practical methods to merge robotics and AI and their validation in the challenging field of robot-assisted surgery. Instrumental to achieving the project results was the availability of the da Vinci Research Kit (dVRK). It permitted to span most of the aspects of robot-assisted surgery, such as knowledge representation, medical image processing, software engineering, robotic control, human-machine interfaces, haptics, and tele-robotics. Each topic was the subject of one or more doctoral dissertations whose main findings are summarized in the dedicated Chapters.
Introduction.- Knowledge Extraction, Representation and Task Planning.- Learning Surgical Procedures from Text.- Surgical Task Planning and Learning.- Towards Surgical Task Planning from Text.- Learning Surgical Gestures from Data.
