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Jockusch, Ján: Exploration based on neural networks with applications in manipulator control. 2000
Inhalt
Introduction
Robotics Lab Setup
Human-Machine Interfacing
Exploration and Control
Previous Work on Robotic Control
Introduction to a Novel Approach
The Controller Architecture
Manipulator and Sensor Hardware
Mechanical Construction
Basic Sensory Equipment
The Tactile Sensor System
The Fingertip Sensors
Construction Principle
Amplification Circuitry
Experimental Results
A Layered Controller Architecture
Design Fundamentals
Levels of Timing and Abstraction
The Controller Layer
The Controller Structure
Mechanisms for Safety and Reliability
Interfacing with Other Processes
Implementation Details
A Visual Controller Interface
Performance Evaluation
The State Machine Layer
The Programming Principle
States and State Transitions
Implementation Details
An Example State Graph
Interleaving State Machines
Conclusions
Exploration with Vector Quantization Networks
Approaching Intertwined Tasks
Introduction
Literal Interpretation of Topological Maps
Evaluation of Existing Models
Critical Aspects in Robotics
Preparation of Input Data
Adaptive Metrics for Input Rescaling
Expansive Adaptation
The Instantaneous Topological Map
Improving the GNG for Correlated Stimuli
The Instantaneous Topological Map (ITM)
Results
Statistical Distributions
Architectural Comparison
Dimensionality of Input Data
Conclusions
Path Finding and Obstacle Avoidance with the ITM
Graph Distance Labeling
Trajectory Generation
Experimental Validation
An Active Exploration Engine
Basic Ingredients
Results
Discussion and Outlook
Uses Beyond Robotics
Future Perspectives of the Control Architecture
Future Perspectives for the ITM
Closing Remarks