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Learning Dynamic Spatial Relations

Learning Dynamic Spatial Relations: The Case of a Knowledge-based Endoscopic Camera Guidance Robot

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Learning Dynamic Spatial Relations: The Case of a Knowledge-based Endoscopic Camera Guidance Robot

Bihlmaier, Andreas

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.

Details

Published by: Springer Vieweg

Publication Date: 2016-08-18

Format: Paperback

ISBN-13: 9783658149130

DOI: 10.1007/978-3-658-14914-7

Dimensions: 210cm x148cm

Pages: 267

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