Robot Learning by Visual Observation

Table of contents

1. Cover
2. Title Page
3. Preface
4. List of Abbreviations
5. 1 Introduction
   1. 1.1 Robot Programming Methods
   2. 1.2 Programming by Demonstration
   3. 1.3 Historical Overview of Robot PbD
   4. 1.4 PbD System Architecture
   5. 1.5 Applications
   6. 1.6 Research Challenges
   7. 1.7 Summary
   8. References
6. 2 Task Perception
   1. 2.1 Optical Tracking Systems
   2. 2.2 Vision Cameras
   3. 2.3 Summary
   4. References
7. 3 Task Representation
   1. 3.1 Level of Abstraction
   2. 3.2 Probabilistic Learning
   3. 3.3 Data Scaling and Aligning
   4. 3.4 Summary
   5. References
8. 4 Task Modeling
   1. 4.1 Gaussian Mixture Model (GMM)
   2. 4.2 Hidden Markov Model (HMM)
   3. 4.3 Conditional Random Fields (CRFs)
   4. 4.4 Dynamic Motion Primitives (DMPs)
   5. 4.5 Summary
   6. References
9. 5 Task Planning
   1. 5.1 Gaussian Mixture Regression
   2. 5.2 Spline Regression
   3. 5.3 Locally Weighted Regression
   4. 5.4 Gaussian Process Regression
   5. 5.5 Summary
   6. References
10. 6 Task Execution
    1. 6.1 Background and Related Work
    2. 6.2 Kinematic Robot Control
    3. 6.3 Vision‐Based Trajectory Tracking Control
    4. 6.4 Image‐Based Task Planning
    5. 6.5 Robust Image‐Based Tracking Control
    6. 6.6 Discussion
    7. 6.7 Summary
    8. References
11. Index
12. End User License Agreement