Bihlmaier Learning Dynamic Spatial Relations

The Case of a Knowledge-based Endoscopic Camera Guidance Robot
1. Auflage 2016
ISBN: 978-3-658-14914-7
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 267 Seiten, eBook

Andreas Bihlmaier describes a novel method to model dynamic spatial relations by machine learning techniques. The method is applied to the task of representing the tacit knowledge of a trained camera assistant in minimally-invasive surgery. The model is then used for intraoperative control of a robot that autonomously positions the endoscope. Furthermore, a modular robotics platform is described, which forms the basis for this knowledge-based assistance system. Promising results from a complex phantom study are presented.

Zielgruppe

Research

Autoren/Hrsg.

Bihlmaier, Andreas

Inhaltsverzeichnis

Endoscope Robots and Automated Camera Guidance.- Knowledge-based Cognitive Systems.- Modular Research Platform for Robot-Assisted Surgery based on ROS.- Learning of Surgical Know-how by Models of Spatial Relations.- Intraoperative Camera Assistance.- Evaluation Study: TME in the Open Source Heidelberg Laparoscopic Phantom (OpenHELP).

Über Autor(innen)

Andreas Bihlmaier is leader of the Cognitive Medical Technologies group in the Institute for Anthropomatics and Robotics – Intelligent Process Control and Robotics Lab (IAR-IPR) at the Karlsruhe Institute of Technology (KIT). His research focuses on cognitive surgical robotics for minimally-invasive surgery, as part of the SFB/Transregio 125 “Cognition-Guided Surgery”.