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Road Terrain Classification Technology for Autonomous Vehicle, Wang Shifeng


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Цена: 13974.00р.
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Автор: Wang Shifeng
Название:  Road Terrain Classification Technology for Autonomous Vehicle
ISBN: 9789811361579
Издательство: Springer
Классификация:




ISBN-10: 9811361576
Обложка/Формат: Paperback
Страницы: 97
Вес: 0.17 кг.
Дата издания: 14.08.2020
Серия: Unmanned system technologies
Язык: English
Издание: 1st ed. 2019
Иллюстрации: 53 tables, color; 32 illustrations, color; 11 illustrations, black and white; xvi, 97 p. 43 illus., 32 illus. in color.
Размер: 23.39 x 15.60 x 0.61 cm
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book provides cutting-edge insights into autonomous vehicles and road terrain classification, and introduces a more rational and practical method for identifying road terrain.


Road Terrain Classification Technology for Autonomous Vehicle

Автор: Shifeng Wang
Название: Road Terrain Classification Technology for Autonomous Vehicle
ISBN: 9811361541 ISBN-13(EAN): 9789811361548
Издательство: Springer
Рейтинг:
Цена: 13974.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book provides cutting-edge insights into autonomous vehicles and road terrain classification, and introduces a more rational and practical method for identifying road terrain. It presents the MRF algorithm, which combines the various sensors’ classification results to improve the forward LRF for predicting upcoming road terrain types. The comparison between the predicting LRF and its corresponding MRF show that the MRF multiple-sensor fusion method is extremely robust and effective in terms of classifying road terrain. The book also demonstrates numerous applications of road terrain classification for various environments and types of autonomous vehicle, and includes abundant illustrations and models to make the comparison tables and figures more accessible.

Slam Techniques Application for Mobile Robot in Rough Terrain

Автор: Kudriashov Andrii, Buratowski Tomasz, Giergiel Mariusz
Название: Slam Techniques Application for Mobile Robot in Rough Terrain
ISBN: 3030489809 ISBN-13(EAN): 9783030489809
Издательство: Springer
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Цена: 20962.00 р.
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Описание: Introduction.- Robotic inspection of pipelines.- Design of a pipeline inspection mobile robot with an active adaptation mechanism.- Mathematical modeling of the robot.- Simulations of the robot adaptation and motion in various environments.- Control system design and implementation.- Prototype of the pipe inspection robot.- Discussion, conclusions and future work.

Mobile Robots in Rough Terrain

Автор: Karl Iagnemma; Steven Dubowsky
Название: Mobile Robots in Rough Terrain
ISBN: 3642060269 ISBN-13(EAN): 9783642060267
Издательство: Springer
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Цена: 16977.00 р.
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Описание: This monograph discusses issues related to estimation, control, and motion planning for mobile robots operating in rough terrain, with particular attention to planetary exploration rovers. Specific addressed topics are: wheel terrain interaction modeling, including terrain parameter estimation and wheel terrain contact angle estimation;

3D-Position Tracking and Control for All-Terrain Robots

Автор: Pierre Lamon
Название: 3D-Position Tracking and Control for All-Terrain Robots
ISBN: 3642096948 ISBN-13(EAN): 9783642096945
Издательство: Springer
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Цена: 16977.00 р.
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Описание: This book shows how to improve accuracy of position tracking, viewing rough terrain locomotion as a holistic problem. Proposes a mechanical structure allowing smooth motion over obstacles with limited wheel slip, using sensors which improve position estimates.

Creating Autonomous Vehicle Systems

Автор: Liu Shaoshan, Li Liyun, Tang Jie
Название: Creating Autonomous Vehicle Systems
ISBN: 1681739372 ISBN-13(EAN): 9781681739373
Издательство: Mare Nostrum (Eurospan)
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Цена: 13583.00 р.
Наличие на складе: Нет в наличии.

Описание:

This book is one of the first technical overviews of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences designing autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions as to its future actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, new algorithms can be tested so as to update the HD map--in addition to training better recognition, tracking, and decision models.

Since the first edition of this book was released, many universities have adopted it in their autonomous driving classes, and the authors received many helpful comments and feedback from readers. Based on this, the second edition was improved by extending and rewriting multiple chapters and adding two commercial test case studies. In addition, a new section entitled "Teaching and Learning from this Book" was added to help instructors better utilize this book in their classes. The second edition captures the latest advances in autonomous driving and that it also presents usable real-world case studies to help readers better understand how to utilize their lessons in commercial autonomous driving projects.

This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technology stack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find extensive references for an effective, deeper exploration of the various technologies.

Creating Autonomous Vehicle Systems

Автор: Liu Shaoshan, Li Liyun, Tang Jie
Название: Creating Autonomous Vehicle Systems
ISBN: 1681739356 ISBN-13(EAN): 9781681739359
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 10672.00 р.
Наличие на складе: Нет в наличии.

Описание:

This book is one of the first technical overviews of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences designing autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions as to its future actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, new algorithms can be tested so as to update the HD map--in addition to training better recognition, tracking, and decision models.

Since the first edition of this book was released, many universities have adopted it in their autonomous driving classes, and the authors received many helpful comments and feedback from readers. Based on this, the second edition was improved by extending and rewriting multiple chapters and adding two commercial test case studies. In addition, a new section entitled "Teaching and Learning from this Book" was added to help instructors better utilize this book in their classes. The second edition captures the latest advances in autonomous driving and that it also presents usable real-world case studies to help readers better understand how to utilize their lessons in commercial autonomous driving projects.

This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technology stack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find extensive references for an effective, deeper exploration of the various technologies.

Fuzzy Logic Techniques for Autonomous Vehicle Navigation

Автор: Dimiter Driankov; Alessandro Saffiotti
Название: Fuzzy Logic Techniques for Autonomous Vehicle Navigation
ISBN: 3790824798 ISBN-13(EAN): 9783790824797
Издательство: Springer
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Цена: 30606.00 р.
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Описание: In the past decade a critical mass of work that uses fuzzy logic for autonomous vehicle navigation has been reported.

Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings

Автор: Thuy T. Pham
Название: Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings
ISBN: 3030075184 ISBN-13(EAN): 9783030075187
Издательство: Springer
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Цена: 16769.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book describes efforts to improve subject-independent automated classification techniques using a better feature extraction method and a more efficient model of classification. It evaluates three popular saliency criteria for feature selection, showing that they share common limitations, including time-consuming and subjective manual de-facto standard practice, and that existing automated efforts have been predominantly used for subject dependent setting. It then proposes a novel approach for anomaly detection, demonstrating its effectiveness and accuracy for automated classification of biomedical data, and arguing its applicability to a wider range of unsupervised machine learning applications in subject-independent settings.

A General Model of Legged Locomotion on Natural Terrain

Автор: David J. Manko
Название: A General Model of Legged Locomotion on Natural Terrain
ISBN: 1461365880 ISBN-13(EAN): 9781461365884
Издательство: Springer
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Цена: 6986.00 р.
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Описание: Dynamic modeling is the fundamental building block for mechanism analysis, design, control and performance evaluation. The model was applied to a prototype walking machine, and simulations generated significant insights into walking machine performance on natural terrain.

Deep Learning for Autonomous Vehicle Control: Algorithms, State-of-the-Art, and Future Prospects

Автор: Kuutti Sampo, Fallah Saber, Bowden Richard
Название: Deep Learning for Autonomous Vehicle Control: Algorithms, State-of-the-Art, and Future Prospects
ISBN: 1681736160 ISBN-13(EAN): 9781681736167
Издательство: Mare Nostrum (Eurospan)
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Цена: 8593.00 р.
Наличие на складе: Нет в наличии.

Описание: The CAFE system has changed the way teachers assess, teach, and track student information, and positively impacted the way students learn. This updated, second edition demonstrates that reading instruction is not about the setting, the basal, or the book level. Rather, effective reading instruction is based on what the student needs in the moment.

Deep Learning for Autonomous Vehicle Control: Algorithms, State-of-the-Art, and Future Prospects

Автор: Kuutti Sampo, Fallah Saber, Bowden Richard
Название: Deep Learning for Autonomous Vehicle Control: Algorithms, State-of-the-Art, and Future Prospects
ISBN: 1681736071 ISBN-13(EAN): 9781681736075
Издательство: Mare Nostrum (Eurospan)
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Цена: 6237.00 р.
Наличие на складе: Нет в наличии.

Описание: The next generation of autonomous vehicles will provide major improvements in traffic flow, fuel efficiency, and vehicle safety. Several challenges currently prevent the deployment of autonomous vehicles, one aspect of which is robust and adaptable vehicle control. Designing a controller for autonomous vehicles capable of providing adequate performance in all driving scenarios is challenging due to the highly complex environment and inability to test the system in the wide variety of scenarios which it may encounter after deployment. However, deep learning methods have shown great promise in not only providing excellent performance for complex and non-linear control problems, but also in generalizing previously learned rules to new scenarios. For these reasons, the use of deep neural networks for vehicle control has gained significant interest. In this book, we introduce relevant deep learning techniques, discuss recent algorithms applied to autonomous vehicle control, identify strengths and limitations of available methods, discuss research challenges in the field, and provide insights into the future trends in this rapidly evolving field.

Canonical Instabilities of Autonomous Vehicle Systems

Автор: Rodrick Wallace
Название: Canonical Instabilities of Autonomous Vehicle Systems
ISBN: 3319699342 ISBN-13(EAN): 9783319699349
Издательство: Springer
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Цена: 10480.00 р.
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Описание: The asymptotic limit theorems of control and information theories make it possible to explore the dynamics of collapse likely to afflict large-scale systems of autonomous ground vehicles that communicate with each other and with an embedding intelligent roadway.


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