Navigation with Local Sensors in Surgical Robotics

Using robots in medicine and especially in surgery requires an adequate representation of and reaction to a changing environment. This is usually achieved by modeling the environment at different representation levels throughout the process, ranging from complex 3D imaging modalities which reflect the environment geometry to finding appropriate low-level control parameters for actual motion through environment regions. In this work, a common framework for different types of navigational problems in surgical robotics is proposed, and validated by the introduction of navigation cycles on novel local sensors. Currently industrial (and surgical) robotic systems employ almost exclusively static global maps -- if any -- for navigation and planning purposes. Additional information -- intra-process, spatial, current, and persistent sensor data -- is useful to cope with uncertainty, measurement errors, and incompleteness of data. Between global pre-operative navigation and control, this work introduces the concept of intra-operative navigation on local sensor data into surgical robotics. This includes the creation and maintenance (both concurrent as well as independent) of local environment maps for navigation purposes. This intermediate level of sensory feedback and processing allows to react to changes in the environment, based on persistent but incremental mapping. Furthermore, local sensors permit intra-operative sampling of additional information which may be unattainable before process execution, or available only with reduced precision. This work proposes to augment robot world models by introducing such local sensors (in particular, force and sound as well as ultrasonic sensors, all of which provide data from an estimated local epsilon-environment) and to build precise maps from local sensors, which serve as input for several introduced navigation algorithms. This map-building is improved by precise data localisation and precise data insertion. The general idea of nested control loops is illustrated on the basis of a specific surgical application -- robot-based milling at the lateral skull base.

Level thesis:degree_level

thesis.doctoral

Grantor dc:publisher

Universität Bayreuth

Year

2011

Author dc:creator

• Stolka, Philipp J.

Contributors dc:contributor

• Henrich, Dominik

Repository record source_url

https://epub.uni-bayreuth.de/id/eprint/302/

OAI identifier oai:identifier

oai:epub.uni-bayreuth.de:302