Artificial Intelligence for Future Generation Robotics offers a vision for potential future robotics applications for AI technologies. Each chapter includes theory and mathematics to stimulate novel research directions based on the state-of-the-art in AI and smart robotics. Organized by application into ten chapters, this book offers a practical tool for researchers and engineers looking for new avenues and use-cases that combine AI with smart robotics. As we witness exponential growth in automation and the rapid advancement of underpinning technologies, such as ubiquitous computing, sensing, intelligent data processing, mobile computing and context aware applications, this book is an ideal resource for future innovation.

Brings AI and smart robotics into imaginative, technically-informed dialogue
Integrates fundamentals with real-world applications
Presents potential applications for AI in smart robotics by use-case
Gives detailed theory and mathematical calculations for each application
Stimulates new thinking and research in applying AI to robotics

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Yes, you can access Artificial Intelligence for Future Generation Robotics by Rabindra Nath Shaw,Ankush Ghosh,Valentina Emilia Balas,Monica Bianchini in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Robotics. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Elsevier

Year

2021

ISBN

9780323857994

Topic

Technology & Engineering

Subtopic

Robotics

Index

Technology & Engineering

Cover image
Title page
Table of Contents
Copyright
List of contributors
About the editors
Preface
Chapter One. Robotic process automation with increasing productivity and improving product quality using artificial intelligence and machine learning
Chapter Two. Inverse kinematics analysis of 7-degree of freedom welding and drilling robot using artificial intelligence techniques
Chapter Three. Vibration-based diagnosis of defect embedded in inner raceway of ball bearing using 1D convolutional neural network
Chapter Four. Single shot detection for detecting real-time flying objects for unmanned aerial vehicle
Chapter Five. Depression detection for elderly people using AI robotic systems leveraging the Nelder–Mead Method
Chapter Six. Data heterogeneity mitigation in healthcare robotic systems leveraging the Nelder–Mead method
Chapter Seven. Advance machine learning and artificial intelligence applications in service robot
Chapter Eight. Integrated deep learning for self-driving robotic cars
Chapter Nine. Lyft 3D object detection for autonomous vehicles
Chapter Ten. Recent trends in pedestrian detection for robotic vision using deep learning techniques
Index