book

Artificial Intelligence for Future Generation Robotics

by Rabindra Nath Shaw, Ankush Ghosh, Valentina Emilia Balas, Monica Bianchini

June 2021

Intermediate to advanced

178 pages

4h 34m

English

Elsevier

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Abstract1.1 Introduction1.2 Related work1.3 Proposed work1.4 Proposed model1.5 Manufacturing systems1.6 Results analysis1.7 Conclusions and future workReferences
Abstract2.1 Introduction2.2 Literature review2.3 Modeling and design2.4 Results and discussions2.5 Conclusions and future workReferences
Abstract3.1 Introduction3.2 2D CNN—a brief introduction3.3 1D convolutional neural network3.4 Statistical parameters for feature extraction3.5 Dataset used3.6 Results3.7 ConclusionReferences

Abstract4.1 Introduction4.2 Related work4.3 Methodology4.4 Results and discussions4.5 ConclusionReferences
Abstract5.1 Introduction5.2 Background5.3 Related work5.4 Elderly people detect depression signs and symptoms5.5 Proposed methodology5.6 Result analysisReferences
Abstract6.1 Introduction6.2 Data heterogeneity mitigation6.3 LSTM-based classification of data6.4 Experiments and results6.5 Conclusion and future workAcknowledgmentReferences
Abstract7.1 Introduction7.2 Literature reviews7.3 Uses of artificial intelligence and machine learning in robotics7.4 Conclusion7.5 Future scopeReferences
Abstract8.1 Introduction8.2 Self-driving program model8.3 Self-driving algorithm8.4 Deep reinforcement learning8.5 ConclusionReferencesFurther reading
Abstract9.1 Introduction9.2 Related work9.3 Dataset distribution9.4 Methodology9.5 Result9.6 ConclusionsReferences
Abstract10.1 Introduction10.2 Datasets and artificial intelligence enabled platforms10.3 AI-based robotic vision10.4 Applications of robotic vision toward pedestrian detection10.5 Major challenges in pedestrian detection10.6 Advanced AI algorithms for robotic vision10.7 Discussion10.8 ConclusionsReferencesFurther reading

Overview

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.