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Machine learning for robotics applic...

Bianchini, Monica.

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Machine learning for robotics applications

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Machine learning for robotics applications/ edited by Monica Bianchini ... [et al.].
其他作者:	Bianchini, Monica.
出版者:	Singapore :Springer Singapore : : 2021.,
面頁冊數:	xii, 168 p. :ill. (some col.), digital ;24 cm.
內容註:	Chapter 1.Manipulation of Standard Link Mechanism for Robotic Application using Artificial Neural Network and PID -- Chapter 2. Machine learning-enabled Human Activity Recognition System for Humanoid robot -- Chapter 3. Hospital Assistance Robots-Control Strategy and Machine Learning Technology -- Chapter 4. Cyber Physical System Fraud Analysis by Mobile Robot -- Chapter 5. Design and Development of an Intelligent Robot for Improving Crop Productivity using Machine Learning -- Chapter 6. Integration of Wireless Sensor Network in Robotics -- Chapter 7. Industry 4.0 and Robotics Automation-New Trends in Cyber Security -- Chapter 8. Digital Transformation in Smart Manufacturing with Industrial Robot through Predictive Data Analysis -- Chapter 9. Surveillance Robot in Cyber Intelligence for Vulnerability Detection -- Chapter 10. Framework and Smart Contract for Blockchain Enabled Certificate verification Sys-tem using Robotics.
Contained By:	Springer Nature eBook
標題:	Machine learning. -
電子資源:	https://doi.org/10.1007/978-981-16-0598-7
ISBN:	9789811605987

Machine learning for robotics applications
Machine learning for robotics applications[electronic resource] /edited by Monica Bianchini ... [et al.]. - Singapore :Springer Singapore :2021. - xii, 168 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.9601860-949X ;. - Studies in computational intelligence ;v.960..

Chapter 1.Manipulation of Standard Link Mechanism for Robotic Application using Artificial Neural Network and PID -- Chapter 2. Machine learning-enabled Human Activity Recognition System for Humanoid robot -- Chapter 3. Hospital Assistance Robots-Control Strategy and Machine Learning Technology -- Chapter 4. Cyber Physical System Fraud Analysis by Mobile Robot -- Chapter 5. Design and Development of an Intelligent Robot for Improving Crop Productivity using Machine Learning -- Chapter 6. Integration of Wireless Sensor Network in Robotics -- Chapter 7. Industry 4.0 and Robotics Automation-New Trends in Cyber Security -- Chapter 8. Digital Transformation in Smart Manufacturing with Industrial Robot through Predictive Data Analysis -- Chapter 9. Surveillance Robot in Cyber Intelligence for Vulnerability Detection -- Chapter 10. Framework and Smart Contract for Blockchain Enabled Certificate verification Sys-tem using Robotics.

Machine learning has become one of the most prevalent topics in recent years. The application of machine learning we see today is a tip of the iceberg. The machine learning revolution has just started to roll out. It is becoming an integral part of all modern electronic devices. Applications in automation areas like automotive, security and surveillance, augmented reality, smart home, retail automation and healthcare are few of them. Robotics is also rising to dominate the automated world. The future applications of machine learning in the robotics area are still undiscovered to the common readers. We are, therefore, putting an effort to write this edited book on the future applications of machine learning on robotics where several applications have been included in separate chapters. The content of the book is technical. It has been tried to cover all possible application areas of Robotics using machine learning. This book will provide the future vision on the unexplored areas of applications of Robotics using machine learning. The ideas to be presented in this book are backed up by original research results. The chapter provided here in-depth look with all necessary theory and mathematical calculations. It will be perfect for laymen and developers as it will combine both advanced and introductory material to form an argument for what machine learning could achieve in the future. It will provide a vision on future areas of application and their approach in detail. Therefore, this book will be immensely beneficial for the academicians, researchers and industry project managers to develop their new project and thereby beneficial for mankind. Original research and review works with model and build Robotics applications using Machine learning are included as chapters in this book.

ISBN: 9789811605987

Standard No.: 10.1007/978-981-16-0598-7doiSubjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5 / .M334 2021

Dewey Class. No.: 006.31

Machine learning for robotics applications
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520 $a Machine learning has become one of the most prevalent topics in recent years. The application of machine learning we see today is a tip of the iceberg. The machine learning revolution has just started to roll out. It is becoming an integral part of all modern electronic devices. Applications in automation areas like automotive, security and surveillance, augmented reality, smart home, retail automation and healthcare are few of them. Robotics is also rising to dominate the automated world. The future applications of machine learning in the robotics area are still undiscovered to the common readers. We are, therefore, putting an effort to write this edited book on the future applications of machine learning on robotics where several applications have been included in separate chapters. The content of the book is technical. It has been tried to cover all possible application areas of Robotics using machine learning. This book will provide the future vision on the unexplored areas of applications of Robotics using machine learning. The ideas to be presented in this book are backed up by original research results. The chapter provided here in-depth look with all necessary theory and mathematical calculations. It will be perfect for laymen and developers as it will combine both advanced and introductory material to form an argument for what machine learning could achieve in the future. It will provide a vision on future areas of application and their approach in detail. Therefore, this book will be immensely beneficial for the academicians, researchers and industry project managers to develop their new project and thereby beneficial for mankind. Original research and review works with model and build Robotics applications using Machine learning are included as chapters in this book.
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