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Queißer, Jeffrey: Multi-modal Skill Memories for Online Learning of Interactive Robot Movement Generation. 2018
Inhalt
List of Figures
List of Tables
Introduction
Motivation
Problem Statement
Related References of the Author
Funding Acknowledgements
Organization of the Dissertation
Skill Represenation & Skill Learning
Background: From Theories of Motor Control to High-Level Skill Learning
A Novel Conceptual Framework for Parameterized Skill Learning
Parameterized Skills for Kinematic Representations
Task-Parameterized Skills
Bootstrapping of Parameterized Skills
Regularization of Reward
Experimental Evaluation of Bootstrapping
Discussion
Efficient Exploration of Parameterized Skills
Optimization in Task Related Manifolds
Hybrid Optimization
Transfer Learning
Parameterized Skills for Compliant & Soft Robots
Compliant & Soft Robots
Robotic Platforms
Inverse EQ-Models for Low-Level Control
Discussion
Parameterized Skills for Control of Complex Robots
Primitive Based Dynamics Representation
Parameterized Skills for Dynamic Action Primitives
Evaluation of the Dynamics Representation
Interaction in Dynamic Environments by Integration of Kinematics and Dynamics
Discussion
Discussion & Conclusion
Outlook
Appendix
Parameter Grid Seach for InverseEquilibrium Model of the Affetto Robot
Parameter Grid Seach for InverseEquilibrium Model of the UR5 Robot
Optimization of Human Demonstrations
Example Task Instances of the Drumming Scenario
Prototype Spectra of Human Demonstrations
Interactive Scenario: Joint Angle Trajectories
Interactive Scenario: Optimized Forward Signals
Interactive Scenario: Sucessful Generalizations
References