Artificial Intelligence for Future Generation Robotics (eBook, ePUB)

Redaktion: Shaw, Rabindra Nath; Bianchini, Monica; Balas, Valentina Emilia; Ghosh, Ankush

• Format: ePub

Produktbeschreibung

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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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 178
• Erscheinungstermin: 19. Juni 2021
• Englisch
• ISBN-13: 9780323857994
• Artikelnr.: 62142086

Autorenporträt

Rabindra Nath Shaw is a Senior Member of IEEE (USA), currently holding the post of Director, International Relations, Galgotias University India. He is an alumnus of the applied physics department, University of Calcutta, India. . He has more than eleven years teaching experience in leading institutes like Motilal Nehru National Institute of Technology Allahabad, India, Jadavpur University and others in UG and PG level. He has successfully organised more than fifteen International conferences as Conference Chair, Publication Chair and Editor. He has published more than fifty Scopus/ WoS/ ISI indexed research papers in International Journals and conference Proceedings. He is the editor of several Springer and Elsevier books. His primary area of research is optimization algorithms and machine learning techniques for power system, IoT Application, Renewable Energy, and power Electronics converters. He also worked as University Examination Coordinator, University MOOC's Coordinator, U

niversity Conference Coordinator and Faculty- In Charge, Centre of Excellence for Power Engineering and Clean Energy Integration.

Ankush Ghosh is presently working as Associate Professor in the School of Engineering and Applied Sciences, The Neotia University, India. He has more than 15 years of experience in Teaching, research as well as industry. He has outstanding research experiences and published more than 80 research papers in International Journal and Conferences. He was a research fellow of the Advanced Technology Cell- DRDO, Govt. of India. He was awarded National Scholarship by HRD, Govt. of India. He received his Ph.D. (Engg.) Degree from Jadavpur University in 2010. His UG and PG teaching assignments include Microprocessor and microcontroller, AI, IOT, Embedded and real time systems etc. He has delivered Invited lecture in a number of international seminar/conferences, refreshers courses, and FDPs. He has guided a large number of M.Tech and Ph.D. students. He is Editorial Board Member of several International Journals.

Inhaltsangabe

1.Robotic process automation with increasing productivity and improving product quality using artificial intelligence and machine learning 2.Inverse kinematics analysis of 7-degree of freedom welding and drilling robot using artificial intelligence techniques 3.Vibration-based diagnosis of defect embedded in inner raceway of ball bearing using 1D convolutional neural network 4.Single shot detection for detecting real-time flying objects for unmanned aerial vehicle 5.Depression detection for elderly people using AI robotic systems leveraging the Nelder-Mead Method 6.Data heterogeneity mitigation in healthcare robotic systems leveraging the Nelder-Mead method 7.Advance machine learning and artificial intelligence applications in service robot 8.Integrated deep learning for self-driving robotic cars 9.Lyft 3D object detection for autonomous vehicles 10.Recent trends in pedestrian detection for robotic vision using deep learning techniques