Neural networks for robotics : an engineering perspective
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| Autori principali: | , , |
|---|---|
| Natura: | Livre numérique |
| Lingua: | Anglais |
| Pubblicazione: |
Boca Raton, FL :
CRC Press/Taylor & Francis Group
[2019].
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| Soggetti: | |
| Accesso online: | Accès INSA CVL |
| Nota: |
6.5 Visual Servo Control L'accès complet à la ressource est réservé aux usagers des établissements qui en ont fait l'acquisition Book Collection (EBSCOhost) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Arana-Daniel, Nancy. Neural Networks for Robotics : An Engineering Perspective., Milton : Chapman and Hall/CRC, 2018 |
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| 041 | 0 | |a eng | |
| 100 | 1 | |a Arana-Daniel, Nancy, |d 19..- | |
| 245 | 1 | 0 | |a Neural networks for robotics : |b an engineering perspective |c Nancy Arana-Daniel, Carlos Lopez-Franco, Alma Y. Alanis. |
| 260 | |a Boca Raton, FL : |b CRC Press/Taylor & Francis Group, |c [2019]. | ||
| 300 | |a 1 ressource en ligne (229 pages). | ||
| 500 | |a 6.5 Visual Servo Control | ||
| 500 | |a L'accès complet à la ressource est réservé aux usagers des établissements qui en ont fait l'acquisition | ||
| 500 | |a Book Collection (EBSCOhost) | ||
| 505 | 0 | |a Cover; Half Title; Title; Copyright; Dedication; Contents; Preface; Abbreviations; Chapter 1 Recurrent High Order Neural Networks for Rough Terrain Cost Mapping; 1.1 Introduction; 1.1.1 Mapping background; 1.2 Recurrent High Order Neural Networks, RHONN; 1.2.1 RHONN order; 1.2.2 Neural network training; 1.2.2.1 Kalman lter; 1.2.2.2 Kalman lter training; 1.2.2.3 Extended Kalman lter-based training algorithm, EKF; 1.3 Experimental Results: Identi cation of Costs Maps Using RHONNs; 1.3.1 Synthetic dynamic environments; 1.3.1.1 Synthetic dynamic random environment number 1-1.3.1.2 Synthetic dynamic random environment number 21.3.1.3 Synthetic dynamic random environment number 3; 1.3.2 Experiments using real terrain maps; 1.3.2.1 Real terrain map: grove environment; 1.3.2.2 Real terrain map: golf course; 1.3.2.3 Real terrain map: forest; 1.3.2.4 Real terrain map: rural area; 1.4 Conclusions; Chapter 2 Geometric Neural Networks for Object Recognition; 2.1 Object Recognition and Geometric Representations of Objects; 2.1.1 Geometric representations and descriptors of real objects; 2.2 Geometric Algebra: An Overview; 2.2.1 The geometric algebra of n-D space-2.2.2 The geometric algebra of 3-D space2.2.3 Conformal geometric algebra; 2.2.4 Hyperconformal geometric algebra; 2.2.5 Generalization of G6; 3 into G2n; n; 2.3 Cli ord SVM; 2.3.1 Quaternion valued support vector classi er; 2.3.2 Experimental results; 2.4 Conformal Neuron and Hyper-Conformal Neuron; 2.4.1 Hyperellipsoidal neuron; 2.4.2 Experimental results; 2.5 Conclusions; Chapter 3 Non-Holonomic Robot Control Using RHONN; 3.1 Introduction; 3.2 RHONN to Identify Uncertain Discrete-Time Nonlinear Systems; 3.3 Neural Identi cation; 3.4 Inverse Optimal Neural Control-3.5 IONC for Non-Holonomic Mobile Robots3.5.1 Robot model; 3.5.2 Wheeled robot; 3.5.2.1 Controller design; 3.5.2.2 Neural identi cation of a wheeled robot; 3.5.2.3 Inverse optimal control of a wheeled robot; 3.5.2.4 Experimental results; 3.5.3 Tracked robot; 3.5.3.1 Controller design; 3.5.3.2 Results; 3.6 Conclusions; Chapter 4 NN for Autonomous Navigation on Non-Holonomic Robots; 4.1 Introduction; 4.2 Simultaneous Localization and Mapping; 4.2.1 Prediction; 4.2.2 Observations; 4.2.3 Status update; 4.3 Reinforcement Learning; 4.4 Inverse Optimal Neural Controller-4.4.1 Planning-Identi er-Controller4.5 Experimental Results; 4.6 Conclusions; Chapter 5 Holonomic Robot Control Using Neural Networks; 5.1 Introduction; 5.2 Optimal Control; 5.3 Inverse Optimal Control; 5.4 Holonomic Robot; 5.4.1 Motor dynamics; 5.4.2 Neural identi cation design; 5.4.3 Control design; 5.4.4 Omnidirectional mobile robot kinematics; 5.5 Visual Feedback; 5.6 Simulation; 5.7 Conclusions; Chapter 6 Neural Network-Based Controller for Unmanned Aerial Vehicles; 6.1 Introduction; 6.2 Quadrotor Dynamic Modeling; 6.3 Hexarotor Dynamic Modeling; 6.4 Neural Network-Based PID | |
| 538 | |a Configuration requise : navigateur internet | ||
| 650 | |a Robots | ||
| 650 | |a Réseaux neuronaux (informatique) | ||
| 700 | 1 | |a López-Franco, Carlos, |d 19..- |4 aut | |
| 700 | 1 | |a Alanis, Alma Y., |d 19..- |4 aut | |
| 776 | 0 | |t Arana-Daniel, Nancy. Neural Networks for Robotics : An Engineering Perspective. |c Milton : Chapman and Hall/CRC, 2018 | |
| 856 | 4 | |5 180339901:677222823 |u https://ezproxy.insa-cvl.fr/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1761362&site=ehost-live |z Accès INSA CVL | |
| 997 | |0 830049 |1 Livre numérique |a Ressource numérique |b INSA |b ENSA |c 0/Bibliothèque numérique/ |c 1/Bibliothèque numérique/Autre ressource numérique/ | ||