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Learning-Based Robot Vision : Principles and Applications :  Principles and Applications - Josef Pauli

Learning-Based Robot Vision : Principles and Applications

Principles and Applications

Paperback Published: June 2001
ISBN: 9783540421085
Number Of Pages: 292

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This book provides the background and introduces a practical methodology for developing autonomous camera-equipped robot systems which solve deliberate tasks in open environments based on their competences acquired from training, interaction, and learning in the real task-relevant world; visual demonstration and neural learning for the backbone for acquiring the situated competences. The author verifies the practicability of the proposed methodology by presenting a structured case study including high-level sub-tasks such as localizing, approaching, grasping, and carrying objects.

Introductionp. 1
Need for New-Generation Robot Systemsp. 1
Paradigms of Computer Vision (CV) and Robot Vision (RV)p. 5
Characterization of Computer Visionp. 5
Ch aracterization of Robot Visionp. 8
Robot Systems versus Autonomous Robot Systemsp. 10
Characterization of a Robot Systemp. 10
Characterization of an Autonomous Robot Systemp. 11
Autonomous Camera-Equipped Robot Systemp. 14
Important Role of Demonstration and Learningp. 15
Learning Feature Compatibilities under Real Imagingp. 15
Learning Feature Manifolds of Real World Situationsp. 18
Learning Environment-Effector-Image Relationshipsp. 20
Compatibilities, Manifolds, and Relationshipsp. 21
Ch apter Overview of th e Workp. 23
Compatibilities for Object Boundary Detectionp. 25
Introduction to th e Ch apterp. 25
General Context of th e Ch apterp. 25
Object Localization and Boundary Extractionp. 27
Detailed Review of Relevant Literaturep. 28
Outline of th e Sections in th e Ch apterp. 31
Geometric/Photometric Compatibility Principlesp. 32
HoughTransformation for Line Extractionp. 32
Orientation Compatibility between Lines and Edgesp. 34
Junction Compatibility between Pencils and Cornersp. 41
Compatibility-Based Structural Level Groupingp. 46
HoughPeaks for Approximate Parallel Linesp. 47
Phase Compatibility between Parallels and Rampsp. 49
Extraction of Regular Quadranglesp. 54
Extraction of Regular Polygonsp. 61
Compatibility-Based Assembly Level Groupingp. 69
Focusing Image Processing on Polygonal Windowsp. 70
Vanishing-Point Compatibility of Parallel Linesp. 74
Pencil Compatibility of Meeting Boundary Linesp. 76
Boundary Extraction for Approximate Polyhedrap. 78
Geometric Reasoning for Boundary Extractionp. 79
Visual Demonstrations for LearningDegrees ofCompatibilityp. 85
LearningDegreeofLine/EdgeOrientationCompatibilityp. 85
LearningDegreeofParallel/RampPhaseCompatibilityp. 90
Learning Degree of Parallelism Compatibilityp. 95
Summary and Discussion of th e Ch apterp. 96
Manifolds for Object and Situation Recognitionp. 101
Introduction to th e Ch apterp. 101
General Context of th e Ch apterp. 101
Approachfor Object and Situation Recognitionp. 102
Detailed Review of Relevant Literaturep. 103
Outline of th e Sections in th e Ch apterp. 108
Learning Pattern Manifolds withGBFs and PCAp. 108
Compatibility and Discriminability for Recognitionp. 108
Regularization Principles and GBF Networksp. 111
Canonical FrameswithPrincipalComponent Analysis.116
GBF Networks for Approximation of Recognition Functionsp. 122
Approachof GBF Network Learning for Recognitionp. 122
Object Recognition under Arbitrary View Anglep. 124
Object Recognition for Arbitrary View Distancep. 129
Scoring of Grasping Situationsp. 131
Making Manifold Approximation Tractablep. 134
Log-Polar Transformation for Manifold Simplification.137
Space-Time Correlations for Manifold Refinementp. 145
Learning Strategy withPCA/GBF Mixturesp. 154
Summary and Discussion of th e Ch apterp. 168
Learning-Based Achievement of RV Competencesp. 171
Introduction to th e Ch apterp. 171
General Context of th e Ch apterp. 171
Learning Beh avior-Based Systemsp. 174
Detailed Review of Relevant Literaturep. 178
Outline of th e Sections in th e Ch apterp. 182
Integrating Deliberate Strategies and Visual Feedbackp. 183
Dynamical Systems and Control Mechanismsp. 183
Generic Modules for System Developmentp. 197
Treatment of an Exemplary High-Level Taskp. 206
Description of an Exemplary High-Level Taskp. 206
Localization of a Target Object in the Imagep. 208
Determining and Reconstructing Obstacle Objectsp. 213
Approaching and Grasping Obstacle Objectsp. 219
Clearing Away Obstacle Objects on a Parking Areap. 225
Inspection and/or Manipulation of a Target Objectp. 231
Monitoring the Task-Solving Processp. 237
Overall Task-Specific Configuration of Modulesp. 238
Basic Mechanisms for Camera-Robot Coordinationp. 240
Camera-Manipulator Relation for One-Step Controlp. 240
Camera-Manipulator Relation for Multi-step Control.245
Hand Servoing for Determining the Optical Axisp. 248
Determining th e Field of Sh arp Viewp. 250
Summary and Discussion of th e Ch apterp. 252
Summary and Discussionp. 255
Developing Camera-Equipped Robot Systemsp. 255
Rationale for th e Contents of Th is Workp. 258
Proposals for Future Research Topicsp. 260
Ellipsoidal Interpolationp. 263
Further Behavioral Modulesp. 265
Symbolsp. 269
Indexp. 273
Referencesp. 277
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9783540421085
ISBN-10: 3540421084
Series: Lecture Notes in Computer Science
Audience: General
Format: Paperback
Language: English
Number Of Pages: 292
Published: June 2001
Publisher: Springer-Verlag Berlin and Heidelberg Gmbh & Co. Kg
Country of Publication: DE
Dimensions (cm): 23.39 x 15.6  x 1.63
Weight (kg): 0.43