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Neural Systems for Robotics.
Neural Systems for Robotics represents the most up-to-date developments in the rapidly growing aplication area of neural networks, which is one of the hottest application areas for neural networks technology. The book not only contains a comprehensive study of neurocontrollers in complex Robotics sy...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Academic Press
1997.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Front Cover; Neural Systems for Robotics; Copyright Page; Table of Contents; Contributors; Preface; Chapter 1. Neural Network Sonar as a Perceptual Modality for Robotics; 1.1 Use of Sonar in Robotics; 1.2 Echolocating Bats; 1.3 Neural Network Models of Biosonar; 1.4 A Neural Network That Recognizes Speed of Movement; 1.5 Conclusion; Chapter 2. Dynamic Balance of a Biped Walking Robot; 2.1 Introduction; 2.2 Background; 2.3 Methods; 2.4 Results; 2.5 Conclusion; Chapter 3. Visual Feedback in Motion; 3.1 Introduction; 3.2 The Trajectory of an Eye-in-Hand System
- 3.3 The Time-Independent Constraints3.4 The Time-Dependent Constraints; 3.5 Visual Measurement of the Stopping Criteria; 3.6 Controlling the Manipulator; 3.7 Results; 3.8 Discussion; 3.A Derivation of the Stopping Criteria; 3.B Proof of Theorem 3.2; 3.C Nonlinear Transform of a Noisy Signal; Chapter 4. Inverse Kinematics of Dextrous Manipulators; 4.1 Introduction; 4.2 Kinematics; 4.3 Solving the Inverse Kinematics Problem
- A Survey; 4.4 Exploiting Global Topological Knowledge to Solve the Inverse Kinematics Problem; 4.5 Future Research Directions; 4.6 Conclusion
- Chapter 5. Stable Manipulator Trajectory Control Using Neural N etworks5.1 Introduction; 5.2 Neural Networks; 5.3 Methodology; 5.4 Neural Network Offline Learning; 5.5 Control Structure and Neural Network Online Learning Algorithm
- Method 1; 5.6 Control Structure and Neural Network Online Learning Algorithm-Method 2; 5.7 Discussions of Online and Offline Learning; 5.8 Applications in a PUMA Robot; 5.9 Conclusion; 5.A Proof of Theorem 5.4; 5.B Proof of Theorem 5.5; 5.C Proof of Theorem 5.6; 5.D Proof of Theorem 5.7; Chapter 6. The Neural Dynamics Approach to Sensory-Motor Control
- 6.1 Introduction6.2 Neural Models of Biological Motor Control; 6.3 Unsupervised Control of a Mobile Robot; 6.4 The DIVA Model of Speech Production; 6.5 Conclusion; Chapter 7. Operant Conditioning in Robots; 7.1 Introduction; 7.2 Mobile Robots, AI, and Conditioning; 7.3 Neural Models of Conditioning; 7.4 Conditioning Models and Robot Control; 7.5 Implementation in Robots; 7.6 Discussion; Chapter 8. A Dynamic Net for Robot Control; 8.1 Introduction; 8.2 Background; 8.3 The Neuro-Connector Model of Learning and Motivation; 8.4 The Net in Operation; 8.5 Implementation on a Mobile Robot
- 8.6 Simulation Experiments8.7 The Appropriateness of Using the Neuro-Connector Model as a Robot Controller; 8.8 Conclusion; 8.A Sensory Conditions; 8.B Behaviors; 8.C Sensory Neuron Parameters; 8.D Releaser Neuron Parameters; 8.E Behavior Neuron Parameters; 8.F Synaptic Parameters; Chapter 9. Neural Vehicles; 9.1 Introduction; 9.2 Reactive Navigation; 9.3 Planned Navigation in Known Environments; 9.4 Map Building; 9.5 Conclusion; Chapter 10. Self-Organization and Autonomous Robots; 10.1 Introduction; 10.2 Hypothesis; 10.3 AI and Autonomous Robots; 10.4 Realizations of Action-Oriented Systems