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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 |
MARC
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| 245 | 0 | 0 | |a Neural Systems for Robotics. |
| 260 | |b Academic Press |c 1997. | ||
| 300 | |a 1 online resource (369 pages) | ||
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| 520 | |a 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 systems, written by highly respected researchers in the field but outlines a novel approach to solving Robotics problems. The importance of neural networks in all aspects of Robot arm manipulators, neurocontrol, and Robotic systems is also given thorough and in-depth coverage. All researchers and students dealing with Robotics will find Neural Systems for Robotics of immense interest and assistance. Key Features * Focuses on the use of neural networks in robotics-one of the hottest application areas for neural networks technology * Represents the most up-to-date developments in this rapidly growing application area of neural networks * Contains a new and novel approach to solving Robotics problems. | ||
| 505 | 0 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 650 | 0 | |a Robots |x Control systems. | |
| 650 | 0 | |a Neural networks (Computer science) | |
| 650 | 2 | |a Neural Networks, Computer |0 (DNLM)D016571 | |
| 650 | 6 | |a Robots |x Syst�emes de commande. |0 (CaQQLa)201-0193987 | |
| 650 | 6 | |a R�eseaux neuronaux (Informatique) |0 (CaQQLa)201-0209597 | |
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| 650 | 7 | |a Neural networks (Computer science) |2 fast |0 (OCoLC)fst01036260 | |
| 650 | 7 | |a Robots |x Control systems |2 fast |0 (OCoLC)fst01099044 | |
| 650 | 7 | |a Neuronales Netz |2 gnd |0 (DE-588)4226127-2 | |
| 650 | 7 | |a Roboter |2 gnd |0 (DE-588)4050208-9 | |
| 650 | 7 | |a Regelungssystem |2 gnd |0 (DE-588)4134712-2 | |
| 650 | 7 | |a �Rseaux neuronaux. |2 ram | |
| 700 | 1 | |a Smagt, Patrick van der. |4 aut | |
| 720 | |a Omidvar, Omid. | ||
| 856 | 4 | 0 | |u https://sciencedirect.uam.elogim.com/science/book/9780080925097 |z Texto completo |