Navigation with Local Sensors in Surgical Robotics [Elektronische Ressource] / Philipp J. Stolka. Betreuer: Dominik Henrich
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Navigation with Local Sensors in Surgical Robotics [Elektronische Ressource] / Philipp J. Stolka. Betreuer: Dominik Henrich

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Navigation with Local Sensors in Surgical Robotics Von der Universität Bayreuth zur Erlangung des Grades eines Doktors der Naturwissenschaften (Dr. rer. nat.) genehmigte Abhandlung vorgelegt von Philipp Stolka aus Tychy/Polen 1. Gutachter: 2. Gutachter: Tag der Einreichung: Tag des Kolloquiums: 23Prefix•About800,JabiribnHayyan,laterknownasGeber,waseducated reading translationsfrom Greek and based his chemical system ”on two substances: sulphur, which...is hotand dry, and mercury, which is cold and wet. Since each contains all four elements, anyother material can be formed by the proper combination of these two, and since we cannotknow substance but only form, our search must aim at the most desired product, gold”.This is the most perfect, most virtuous product since, as Aristotle said, all things, evenbase metals, struggle upward.•”Todotwothingsatonceistodoneither.”–PubliliusSyrus,Romanslave,firstcenturyB.C.•”Thepastonlyexistsinsofarasitispresentintherecordsof today. And what thoserecords are is determined by what questions we ask. There is nootherhistorythanthat.”–JohnA.Wheler,19824AbstractUsing robots in medicine and especially in surgery requires an adequate representation of andreaction to a changing environment. This is usually achievedbymodelingtheenvironmentat di!

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Published 01 January 2011
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Language English
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Navigation with Local Sensors
in Surgical Robotics





Von der Universität Bayreuth
zur Erlangung des Grades eines
Doktors der Naturwissenschaften (Dr. rer. nat.)
genehmigte Abhandlung



vorgelegt von
Philipp Stolka
aus Tychy/Polen




1. Gutachter:
2. Gutachter:

Tag der Einreichung:
Tag des Kolloquiums: 23
Prefix
•About800,JabiribnHayyan,laterknownasGeber,waseducated reading translations
from Greek and based his chemical system ”on two substances: sulphur, which...is hot
and dry, and mercury, which is cold and wet. Since each contains all four elements, any
other material can be formed by the proper combination of these two, and since we cannot
know substance but only form, our search must aim at the most desired product, gold”.
This is the most perfect, most virtuous product since, as Aristotle said, all things, even
base metals, struggle upward.
•”Todotwothingsatonceistodoneither.”–PubliliusSyrus,Romanslave,firstcentury
B.C.
•”Thepastonlyexistsinsofarasitispresentintherecordsof today. And what those
records are is determined by what questions we ask. There is nootherhistorythanthat.”
–JohnA.Wheler,19824
Abstract
Using robots in medicine and especially in surgery requires an adequate representation of and
reaction to a changing environment. This is usually achievedbymodelingtheenvironment
at di!erent 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 di!erent 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 employalmostexclusivelystaticglobal
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 feed-
back 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
informationwhichmaybeunattainablebeforeprocessexecution, oravailableonlywithreduced
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 esti-
mated local !-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 ofnestedcontrolloopsisilustrated
on the basis of a specific surgical application – robot-based milling at the lateral skull base.
Zusammenfassung
Die Nutzung von Robotern in der Medizin und insbesondere in der Chirurgie erfordert eine
angemessene Darstellung der Umgebung sowie eine entsprechende Reaktion auf sich darin än-
dernde Eigenschaften. Üblicherweise wird dies erreicht durch Umweltmodellierung auf ver-
schiedenen Repräsentationsebenen innerhalb des Prozesses, von komplexen 3D-Bildgebungs-
verfahren, welche die Umweltgeometrie abbilden, bis hin zu Regelungsparametern niedriger
Ebenen für die tatsächliche Bewegung durch die Umgebung. In dieser Arbeit wird ein um-
fassender Rahmen für verschiedene Arten von Navigationsproblemen vorgestellt und anhand
der Einführung von Navigationszyklus basiered auf neuartigen lokalen Sensoren validiert.
Heutzutage verwenden viele industrielle und medizinische Robotersysteme allenfalls statis-
che, globale Karten zur Navigation und Planung. ZusätzlicheInformationen–prozessbezogene,
räumliche, aktuelleundpersistente Sensordaten –sindhilfreich imUmgangmitunsicheren, un-
genauenoderunvollständigen Daten. DieseArbeitstelltdasKonzeptderintra-operativenNav-
igation auf lokalen Sensordaten vor, welches sich zwischen globaler prä-operativer Navigation
und Regelung einordnet. Dies beinhaltet die Erstellung und Aktualisierung von lokalen Umge-
bungskarten für Navigationsaufgaben (sowohl mitlaufend wie auch unabhängig). Diese Zwis-
chenstufe sensorischer Rückkopplung und Verarbeitung erlaubt die Reaktion auf Umweltverän-
derungen basierend auf mitlaufender und persistenter Kartenerstellung. Weiterhin erlauben
lokaleSensorendieintra-operativeAufnahmevonInformation,dievorProzessausführung nicht
oder nur mit verminderter Genauigkeit verfügbar wäre.
Die vorliegende Arbeit schlägt die Erweiterung von Roboter-Weltmodellen mit Hilfe solcher
lokaler Sensoren vor, insbesondere mit Kraft-, Schall- und Ultraschallsensorik und deren Daten5
aus einer zuvor bestimmten lokalen !-Umgebung. Damit werden präzise Karten von lokalen
Sensoren erstellt, die als Eingabe für verschiedene vorgestellte Navigationsalgorithmen dienen.
Diese Kartierung wird optimiert durch genaue Datenlokalisierung und -eintragung. Die allge-
meine Idee verschachtelter Navigationszyklen wird anhand einer konkreten chirurgischen An-
wendung illustriert: robotergestütztem Fräsen an der lateralen Schädelbasis.6
Acknowledgments
This work is a result of the project „Robot-based navigation formilling atthe lateral skull base
(RONAF)“ ofthespecialresearch cluster „Medicalnavigationandrobotics“ (SPP1124)funded
by the Deutsche Forschungsgemeinschaft (DFG) over the years2002through2008,performed
at the
UniversityofBayreuth, ChairforAppliedComputingScienceIII(RoboticsandEm-
beddedSystems)inBayreuth,GermanyunderProf.Dr.DominikHenrich(formerly
at AG Embedded Systems and Robotics/RESY, Technical University of Kaiser-
slautern, Germany),
in cooperation with the
Universitäts-HNO-Klinik (Abt. HNO-Heilkunde) in Heidelberg, Germany under
Prof. Dr. Dr. h.c. P. K. Plinkert with Dr. med. Philippe A. Federspil (formerly at
Universitäts-HNO-Klinik Homburg, University of Saarland,Homburg/Saar,Ger-
many).
Ultrasound-related device development and support was received from the
Fraunhofer Institute for Bio-Medical Technology (FhG IBMT)inSt.Ingbert,Ger-
many, in particular Dipl.-Ing. (FH) Ste!en Tretbar.
Further information about the project can be found at
http://www.ai3.uni-bayreuth.de/projects/ronaf/7
Aus Europa
At this place, I want to express my gratitude to the following:
Dominik ”DCD” Henrich: For being my long-time academic advisor and mentor with lots
(and lots, and then some) of patience.
Philippe A. ”Featherplay” Federspil: For clinical advice and for making ultrasound a pri-
ority.
Ste!en Tretbar: For faith in our experimental setups and for ultrasound.
Friedrich M. Wahl: For being so interested in this work as to agree to become a reviewer.
Michel ”M-Dabbeliu” Waringo: For robot taming and long-time support, collaboration,
and friendship.
Thorsten ”Techno” Gecks: For widening horizons.
AI3/RESY: For being an outstanding lab peer group.
Emad ”LB” M. Boctor & Russell H. Taylor For the awesome opportunity and trust.
N.A.: For the final caring push and constant belief.
The family: For being family, and for insisting.
MM,XX,AC,FW :Forbeinghere,there,forpushing,andsupport(deserved&undeserved).8
Erklärung
Hiermit versichere ich, Philipp J. Stolka, dass ich die von mir vorgelegte Dissertation „Navi-
gation with Local Sensors in Surgical Robotics“ selbständigverfasstundkeineanderenalsdie
angegebenen Quellen und Hilfsmittel verwendet habe.
Declaration
Hereby I, Philipp J. Stolka, declare that this present thesis”NavigationwithLocalSensorsin
Surgical Robotics” was independently authored by meand thatnosourcesandtoolsotherthan
the listed ones have been used.
May 25 2011, Baltimore MD, USA
Date, City Philipp J. StolkaContents
1Introduction 13
1.1 Motivation.......................................13
1.1.1 Evolution of Surgery .........13
1.1.2 Navigation in Robotic Surgery....15
1.2 Problem and Goals ....16
1.2.1 Shortcomings of Current Systems ......................16
1.2.2 Aims of the Present Work ......17
1.3 Task and Contributions............19
1.4 Investigated Application ...............................21
1.4.1 Medical Application .............................22
1.4.2 Technical Constraints23
1.5 Delimitation of Work .............25
1.6 Overview..........26
2StateoftheArt 29
2.1 Classification of Intelligent Tools and Systems in Surgery .............29
2.2 Related Problems and Applications ...............3
2.2.1 Bone Milling Interventions ......3
2.2.2 Surgical Navigation Systems.....3
2.2.3 Registration........................34
2.2.4 Navigation in Robot-Based Systems.....................35
2.2.5 Positioning ..............35
2.2.6 Deformation36
2.2.7 Image-Guided Therapy, Control, and Communications Toolkits .....37
2.2.8 Ear-Nose-Throat and Head/Neck/Neurosurgery ..............38
2.3 Sensors for Surgical Robotics...................39
2.4 Conclusion...................42
3ProposedAproach 45
3.1 Definitions....................45
3.1.1 Sensor Classes.............45
3.1.1.1 Global Sensors .......46
3.1.1.2 Local Sensors ........47
3.1.2 Mapping Process ...............................47
3.1.2.1 Map .................................47
3.1.2.2 Localization.........48
3.1.2.3 Registration48
3.1.2.4 Exploration and Map Building ........49
3.1.3 Planning and Navigation...........................49
3.2 Navigation Cycles in CAS/RAS49
910 CONTENTS
3.2.1 Global Pre-Operative Navigation ......................50
3.2.2 Global Intra-Operative Navigation .....................51
3.2.3 Local Navigation ...............................51
3.2.4 Control ................52
3.3 Hypotheses ............................53
3.3.1 H1: Local Sensors Providing Surgically Relevant Information.......53
3.3.1.1 Claim ..53
3.3.1.2 Experiment Design.....54
3.3.1.3 Expected Gain ...........................55
3.3.2 H2: Map-Building with Local Sensors5
3.3.2.1 Claim ............56
3.3.2.2 Experiment Design.....56
3.3.2.3 Expected Gain ...........................56
3.3.3 H3: Navigation on Maps from Local Sensors......57
3.3.3.1 Claim ............57
3.3.3.2 Experiment Design.....57
3.3.3.3 Expected Gain ...........................58
3.4 System Configurations and Intervention Process Phases....58
3.4.1 System Configurations ........58
3.4.2 Process Phases ............58
3.4.2.1 Phase ”Configuration” .......................59
3.4.2.2 Phase ”Implant Selection” .....................59
3.4.2.3 Phase ”Registration” ....61
3.4.2.4 Phase ”Imaging” ......61
3.4.2.5 Phase ”Implant Position Optimization” ..............61
3.4.2.6 Phase ”Pre-Operative Path Planning”.....61
3.4.2.7 Phase ”Path Execution / Milling” .......61
4LocalSensors 63
4.1 Definition .......................................63
4.1.1 Local Sensors ...64
4.1.2 Tool-based Local Sensors.......65
4.1.3 Destructive Sensing65
4.2 Local Sensors for Surgical Milling Applications...................6
4.2.1 State Identification and Definition............6
4.2.2 Classification Dominance Relation Sets67
4.3 Investigated Local Sensors ..........68
4.3.1 Force/Torque Sensor ...................68
4.3.1.1 Setup ............69
4.3.1.2 F/T Sensor Data Processing70
4.3.1.3 Gravity Compensation...70
4.3.1.4 F/T State Classification ............72
4.3.1.5 F/T Classification Experiments ........72
4.3.1.6 Classification Dominance Relation Sets....73
4.3.2 Audio Sensor .......................73
4.3.2.1 Audio Sensor Data Processing...................75
4.3.2.2 Audio State Classification .....................75
4.3.2.3 Audio Classification Experiments .......75
4.3.3 A-mode Ultrasound....................76
4.3.3.1 Physical Sensor Operation.....................76