Home Page Icon
Home Page
Table of Contents for
Robot Learning by Visual Observation
Close
Robot Learning by Visual Observation
by Farrokh Janabi-Sharifi, Aleksandar Vakanski
Robot Learning by Visual Observation
Cover
Title Page
Preface
List of Abbreviations
1 Introduction
1.1 Robot Programming Methods
1.2 Programming by Demonstration
1.3 Historical Overview of Robot PbD
1.4 PbD System Architecture
1.5 Applications
1.6 Research Challenges
1.7 Summary
References
2 Task Perception
2.1 Optical Tracking Systems
2.2 Vision Cameras
2.3 Summary
References
3 Task Representation
3.1 Level of Abstraction
3.2 Probabilistic Learning
3.3 Data Scaling and Aligning
3.4 Summary
References
4 Task Modeling
4.1 Gaussian Mixture Model (GMM)
4.2 Hidden Markov Model (HMM)
4.3 Conditional Random Fields (CRFs)
4.4 Dynamic Motion Primitives (DMPs)
4.5 Summary
References
5 Task Planning
5.1 Gaussian Mixture Regression
5.2 Spline Regression
5.3 Locally Weighted Regression
5.4 Gaussian Process Regression
5.5 Summary
References
6 Task Execution
6.1 Background and Related Work
6.2 Kinematic Robot Control
6.3 Vision‐Based Trajectory Tracking Control
6.4 Image‐Based Task Planning
6.5 Robust Image‐Based Tracking Control
6.6 Discussion
6.7 Summary
References
Index
End User License Agreement
Search in book...
Toggle Font Controls
Playlists
Add To
Create new playlist
Name your new playlist
Playlist description (optional)
Cancel
Create playlist
Sign In
Email address
Password
Forgot Password?
Create account
Login
or
Continue with Facebook
Continue with Google
Sign Up
Full Name
Email address
Confirm Email Address
Password
Login
Create account
or
Continue with Facebook
Continue with Google
Prev
Previous Chapter
Copyright
Next
Next Chapter
Preface
To our families
Add Highlight
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click
here
login for view all page.
Day Mode
Cloud Mode
Night Mode
Reset