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Gerstmayr-Hillen, Lorenz: From local visual homing towards navigation of autonomous cleaning robots. 2013
Inhalt
Abstract
Zusammenfassung
Acknowledgements
Contents
List of Figures
List of Tables
1 Introduction
1.1 Motivation
1.2 Background of Proposed Work
1.3 Objectives of This Thesis
1.3.1 Vision-Based Trajectory Controller and Mapping
1.3.2 Visual Detection of Already Cleaned Areas
1.4 Outline of This Thesis
2 Cleaning Robots
2.1 Cleaning Robots as Subdomain of Mobile Service Robots
2.2 Domestic Floor-Cleaning Robots
2.2.1 Commercial Products
2.2.2 Academic Research
2.3 Relevance for Our Work
3 Visual Navigation Based on Omnidirectional Images
3.1 Motivation
3.2 Introduction
3.2.1 Definition of Navigation
3.2.2 Basic Categorization of Navigation Methods
3.2.3 Prerequisites for Reliable and Robust Navigation
3.2.4 Omnidirectional Vision
3.3 Representing and Recognizing Places
3.3.1 Representations of Places Based on Omnidirectional Visual Information
3.3.2 Role of Position Information
3.3.3 Discussion of Place Representation and Recognition
3.4 Visual Compass
3.4.1 Definition of Visual Compass
3.4.2 Literature Review on Visual Compass Methods
3.4.3 Discussion of Visual Compass Methods
3.5 Local Visual Homing
3.5.1 Definition of Local Visual Homing
3.5.2 Literature Review on Local Visual Homing
3.5.3 Discussion of Local Visual Homing
3.6 Map-Based Navigation
3.6.1 Definition and Common Principles of Map-Based Navigation
3.6.2 Hierarchical Maps
3.6.3 Literature Review on Quantitative Maps
3.6.4 Literature Review on Qualitative Maps
3.6.5 Discussion of Map-Based Navigation
3.7 Overall Discussion and Outlook
3.7.1 Comparability of Navigation Strategies
3.7.2 Applicability Under Real-World Conditions
3.7.3 Towards Real-World Applications
4 Trajectory Controller Based on Partial Pose Estimation and Dense Topo-Metric Maps
4.1 Introduction
4.1.1 Mapping for Cleaning Robots
4.1.2 Introduction to the Proposed Trajectory Controller
4.2 Dense Topo-Metric Map
4.3 Trajectory Controller
4.3.1 First Lane
4.3.2 Lane Changes
4.3.3 Lane-Distance Estimator
4.3.4 Trajectory Controller
4.4 Experiments and Setup
4.4.1 Procedure and Used Parameters
4.4.2 Min-Warping With Compass Acceleration
4.4.3 Custom-Built Cleaning Robot
4.4.4 Systematic Error
4.4.5 Passive Visual Tracking System
4.4.6 Data Evaluation
4.5 Results
4.5.1 Qualitative Analysis
4.5.2 Inter-Lane Distances
4.5.3 Cleaning Performance
4.6 Discussion and Conclusions
4.6.1 Partial Pose Estimation
4.6.2 Dense Topo-Metric Maps
4.6.3 Influence of Image Disturbances
4.6.4 Implications for Further Cleaning Strategies
4.6.5 Conclusions
4.7 Future Working Directions
5 Holistic Loop-Closure Detection and Visual Compass
5.1 Introduction
5.2 Methods
5.2.1 Image Preprocessing Functions
5.2.2 Global Image Dissimilarity Functions
5.2.3 Accelerated Compass Method Operating in the Fourier Domain
5.2.4 Robustness Against Changes of the Illumination
5.3 Experiments and Evaluation
5.3.1 Experimental Procedure
5.3.2 Evaluation
5.4 Results of Standard Compass Method
5.4.1 Performance of Loop-Closure Detection
5.4.2 Robustness Against Perceptual Aliasing and Perceptual Variability
5.4.3 Compass Accuracy
5.4.4 Computational Aspects of Image Preprocessing Functions
5.4.5 Computational Aspects of Global Image Dissimilarity Functions
5.4.6 Discussion and Conclusions
5.5 Results of Accelerated Compass Method
5.5.1 Performance of Loop-Closure Detection
5.5.2 Compass Accuracy
5.5.3 Computational Aspects
5.5.4 Discussion and Conclusions
5.6 Overall Discussion and Conclusions
5.6.1 Comparison Between Standard and Accelerated Compass Methods
5.6.2 Applicability on a Real Cleaning Robot
5.7 Future Working Directions
5.7.1 Efficient Implementation
5.7.2 Improvement of the Accelerated Compass Variant
5.7.3 Subdivision of the Panoramic Image Into Rings
5.7.4 Testing Further Preprocessing and Image-Dissimilarity Functions
6 Signature-Based Loop-Closure Detection
6.1 Introduction
6.2 Methods
6.2.1 Signature Functions
6.2.2 Dissimilarity Functions
6.2.3 Dimensionality of Signatures
6.2.4 Robustness Against Changes of the Illumination
6.3 Database Experiments
6.3.1 Methods
6.3.2 Results
6.3.3 Discussion and Conclusions
6.4 Real-Robot Experiments
6.4.1 Methods
6.4.2 Results
6.4.3 Discussion and Conclusions
6.5 Overall Discussion and Conclusions
6.6 Future Working Directions
6.6.1 Increasing the Robustness Against Illumination Changes
6.6.2 Integration into a More Complex Control Scheme
6.6.3 Signature-Based Approaches to Topological Mapping
6.6.4 Biological Modeling
7 Overall Summary, Discussion, and Outlook
7.1 Overall Summary
7.2 Overall Discussion
7.2.1 Local Map Consistency vs. Global Map Consistency
7.2.2 Relation of the Proposed Work to Spatial Cognition
7.2.3 Towards a Prototype Product
7.2.4 Alternative Applications for the Proposed Methods
7.3 Future Working Directions
7.3.1 Increasing Robustness Against Dynamic Scene Changes
7.3.2 Towards a Full-Fledged Cleaning Robot Control Scheme
7.3.3 Hierarchical Mapping Based on the Decomposition Into Cleaning Segments
7.3.4 Omnidirectional Vision as Multi-Purpose Sensor
7.3.5 Summary and Appraisal of Future Work
Appendix
A Lane Controller With Partial Position Information
B Panoramic Image Databases
B.1 Example Images
B.2 Positions of Image Acquisition
C Holistic Loop-Closure Detection and Visual Compass
C.1 Derivation of the Distance Measures Proposed by MOELLER10TR1,MOELLER10TR2
C.2 Influence of Linearly Transformed Pixel Intensities on Preprocessed Images
C.3 Influence of Linearly Transformed Pixel Intensities on Image Dissimilarity Functions
C.4 Further Results
D Signature-Based Loop-Closure Detection
D.1 Ground Distance and Relation to `39`42`"613A``45`47`"603AL1-Norm
D.2 Influence of Linearly Transformed Pixel Intensities on Signature Functions
D.3 Further Results
References
Bibliography
Internet Sources
Datasheets and Technical Specifications
Supplemental Materials