Buch, Englisch, 432 Seiten, Format (B × H): 159 mm x 236 mm, Gewicht: 730 g
Buch, Englisch, 432 Seiten, Format (B × H): 159 mm x 236 mm, Gewicht: 730 g
ISBN: 978-1-394-38498-3
Verlag: John Wiley & Sons Inc
Harness the future of automation with this comprehensive guide, offering an in-depth look at how next-generation mobile robotics are driving the transition to a human-centered and sustainable Industry 5.0.
Design and Optimization of Mobile Robotics for Industry 5.0 delivers an in-depth, interdisciplinary look at how next-generation mobile robotic systems are enabling the evolution from Industry 4.0 to a more human-centered, resilient, and sustainable Industry 5.0. This book addresses the technical, ethical, and societal dimensions of robotics technologies, from design principles and autonomous navigation to human-robot interaction and AI integration. It brings together cutting-edge research and real-world case studies across smart manufacturing, agriculture, healthcare, and industrial automation. Readers will explore topics such as digital twins, IoT-enhanced robotics, sensor fusion, and collaborative robotics. With contributions from leading global experts, this volume serves as a comprehensive guide for those involved in designing, deploying, or studying robotics systems that align with the goals of Industry 5.0.
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Preface xvii
Part 1: Foundations of Industry 5.0 and Emerging Technologies 1
1 Advancing Design Principles for Industry 5.0 with a Focus on Human-Centered Innovation 3
Dankan Gowda V., Algubelly Yashwanth Reddy, V. Nuthan Prasad, Ved Srinivas and K.D.V. Prasad
1.1 Introduction 4
1.2 Literature Survey 6
1.3 Core Principles of Human-Centered Design 8
1.4 Technological Advancements Enabling Human-Centered Innovation 10
1.5 Methodologies for Implementing Human-Centered Innovation 13
1.6 Challenges and Barriers to Adoption 15
1.7 Results and Discussion 17
1.8 Future Directions for Research and Practice 21
1.9 Conclusion 21
References 22
2 Methods and Mechanics for Robot Navigation in Different Environments 25
Canute Sherwin, Chandra Singh and Prashanth Kumar
2.1 Introduction 26
2.2 Path Planning 29
2.3 Mobile Robot Navigation Mapping 30
2.3.1 Visual Mapping and Positioning 30
2.3.2 LiDAR Mapping and Positioning 31
2.3.3 Sensor Fusion Mapping and Positioning 31
2.4 Machine Learning 32
2.5 Large Language Models (LLMs) 33
2.5.1 Robot’s Environment Perception 34
2.5.2 High Level Planning 34
2.5.3 Low Level Planning 35
2.5.4 Human–Robot Interaction 36
2.5.5 Multi-Robot Coordination 36
2.6 Deep Learning Approaches 37
2.7 Reinforcement Learning (RL) 39
2.8 Conclusions 40
References 41
3 Detailed Investigation of Autonomous Vehicles in the Context of Industry 5.0 47
C. Sweetline Jenita, E. Fantin Irudaya Raj, S. Sivananaithaperumal and N. Pon Subathira
3.1 Introduction 48
3.2 Self-Driving Systems – Overview 50
3.3 Sensors in Autonomous Vehicle 53
3.3.1 Camera 55
3.3.2 LiDAR 55
3.3.3 Radar 56
3.4 Actuators 57
3.5 Decision-Making Algorithms and Controllers in Self-Driving Systems 59
3.6 Conclusion 61
References 62
4 Emerging Technologies in Industrial Automation with Robotic Applications 67
M. Appadurai, E. Fantin Irudaya Raj, M. Chithambara Thanu and P. Gayathri
4.1 Introduction 68
4.2 Robotics in Additive Manufacturing 68
4.3 Robotic Welding Systems 71
4.4 Digital Twins for Robotic System Optimization 73
4.5 Robotics in Hazardous Environments 75
4.5.1 Robotics in Nuclear Environments 75
4.5.2 Robotics in Space Exploration 76
4.5.3 Robotics in Deep Sea Exploration 76
4.5.4 Robotics in Disaster Response 77
4.6 Robotic Maintenance Systems for Predictive Analytics 77
4.7 Mobile Robotics in Dynamic Industrial Environments 80
4.8 Conclusion 82
References 82
Part 2: Robotics and Mobile Integration in Industry 5.0 87
5 IoT and Mobile Robotics Integration for Transforming Smart Manufacturing in Industry 5.0 89
Dankan Gowda V., Priya Dongare-Jadhav, Noushad Yashan, Madan Mohanrao Jagtap and Suganthi Neelagiri
5.1 Introduction 90
5.1.1 Context and Motivation 90
5.1.2 Role of IoT and Mobile Robotics 92
5.1.3 Objectives of the Chapter 92
5.2 Industry 5.0: A Paradigm Shift 93
5.2.1 Industry 5.0 Vs. Industry 4.0 93
5.2.2 Core Principles of Industry 5.0 94
5.2.3 Technological Advancements Driving Industry 5.0 95
5.3 The Role of IoT in Smart Manufacturing 97
5.3.1 IoT Architecture 97
5.3.2 Applications of IoT in Manufacturing 97
5.3.3 IoT-Enabled Smart Factory 98
5.4 Mobile Robotics in Manufacturing 98
5.4.1 Types of Mobile Robots 98
5.4.2 Key Functions of Mobile Robotics 99
5.4.3 Human-Robot Collaboration 99
5.4.4 Technological Integration 100
5.5 Integration of IoT and Mobile Robotics in Smart Manufacturing 100
5.5.1 Challenges in Integration 100
5.5.2 Framework for Integration 101
5.5.3 Data Sharing and Real-Time Communication 101
5.5.4 Use Case: Real-Time Monitoring and Control 101
5.6 Case Studies and Applications 102
5.6.1 Global Industry Examples 102
5.6.2 Benefits Achieved 102
5.6.3 Lessons Learned 102
5.7 Results and Discussion 103
5.7.1 Key Findings from Literature and Case Studies 103
5.7.2 Impact on Manufacturing Efficiency and Flexibility 103
5.7.3 Human-Centric Manufacturing and Worker Empowerment 105
5.7.4 Sustainability and Environmental Impact 106
5.8 Challenges in the Integration of IoT and Mobile Robotics 109
5.8.1 Technical and Operational Barriers 109
5.8.2 Scalability Issues 109
5.8.3 Standardization and Interoperability 110
5.9 Future Trends and Research Directions 110
5.9.1 AI and Machine Learning Integration 110
5.9.2 5G and Edge Computing 111
5.9.3 Cyber-Physical Systems and Digital Twins 111
5.10 Conclusion 111
References 112
6 Innovative Approaches to Designing and Optimizing Mobile Robotics for Advanced Collaboration in Industry 5.0 115
Mandeep Kaur, P. Arockia Mary, Dankan Gowda V., L.R. Sujithra and Priya Dongare Jadhav
6.1 Introduction 116
6.2 Technological Foundations of Mobile Robotics in Industry 5.0 118
6.3 Literature Survey 120
6.4 Proposed Innovative Approaches to Mobile Robotics Design 123
6.5 Mobile Robotics for Advanced Collaboration 125
6.6 Case Studies 128
6.7 Results and Discussion 131
6.8 Conclusion 134
References 135
7 Applications and Challenges of Digital Twins in Industry 5.0
for Advanced Industrial Systems 139
Dankan Gowda V., Galiveeti Poornima, Kottala Sri Yogi, Madan Mohanrao Jagtap and Shekhar R.
7.1 Introduction 140
7.2 Literature Survey 142
7.3 Framework of Digital Twins in Industry 5.0 144
7.4 Applications of Digital Twins 146
7.5 Challenges in Implementing Digital Twins 149
7.6 Results and Discussion 151
7.7 Conclusion 155
References 155
8 Mobile Robotics for Agriculture: Design and Implementation of an Autonomous Robo-Snake 159
Chandra Singh, Rathishchandra R. Gatti, K.V.S.S.S.S. Sairam and D.K. Sreekantha Karanam Desai
8.1 Introduction 160
8.2 Literature Survey 161
8.3 Problem Statement 166
8.4 Objectives 167
8.5 Methodology 167
Conclusion 171
References 171
Part 3: Human-Robot Collaboration and Interaction 173
9 Synergistic Thinking: Human–Robot Partnership for Smarter Decisions 175
Chandra Singh, Rathishchandra R. Gatti, Ganesha H. S. Harve, K.V.S.S.S.S. Sairam, Durga Prasad and Pavithra Poornima
9.1 Introduction to Human–Robot Collaboration in Mobile Robotics 176
9.1.1 Importance of AI Algorithms in Mobile Robotics 177
9.2 Fundamentals of Decision Making in Mobile Robots 178
9.3 Emerging Technologies in Mobile Robotics 180
9.4 Cooperation Strategies 181
9.5 Applications in Mobile Robotics 182
9.6 Conclusion 184
Bibliography 184
10 Collaborative Robotics in Factory 5.0: Redefining Modern Production 187
Chandra Singh, Rathishchandra R. Gatti, Ganesha H. S. Harve, K.V.S.S.S.S. Sairam, Durga Prasad and Pavithra Poornima
Introduction to Factory 5.0 188
Collaborative Robots (Cobots) and AI in Factory 5.0 189
Augmented Reality (AR) and Virtual Reality (VR) 189
Human-Centric Design in Factory 5.0 190
Applications in Human–Robot Collaboration 191
Logistics and Warehousing 191
Logistics: Amazon’s Robotic Fulfillment Centers 191
Challenges and Opportunities in Human–Robot Collaboration for Factory 5.0 191
Applications of Cobots 195
Future Trends in Cobot Technology 195
Conclusion 196
References 196
11 Human–Robot Interaction in Industry 5.0 199
Babitha Hemanth, Kripa T., Sumiksha Shetty and Smitha A. B.
11.1 Importance of Human–Robot Interaction 200
11.2 Growth of Artificial Intelligence and Machine Learning for Mobile Robots 201
11.2.1 Intelligence-Driven Customization and Optimization in Autonomous Mobile Robotics 202
11.3 Integration with Emerging Technologies 203
11.4 Synergy with IoT 204
11.4.1 Mobile Robots Integrated with IoT for Enhanced Communication and Data Sharing Across Industrial Systems 204
11.4.2 Benefits of IoT-Enabled Mobile Robots in Real-Time Monitoring and Coordination 205
11.5 Blockchain for Data Security 207
11.5.1 Using Blockchain to Ensure Secure Data Transactions and Communication Between Mobile Robots and Other Industrial Systems 207
11.6 Enhanced Connectivity 208
11.6.1 Advanced Connectivity Technologies (e.g., 5G) Improving the Performance and Coordination of Mobile Robots in Dynamic Environments 208
11.7 Human-Centric Innovations in Mobile Robotics 209
11.8 Improving Human Well-Being and Job Satisfaction 209
11.8.1 Alleviating Physical Strain: What Human Employees Gain from Mobile Robots Support in Terms of Redundant or Unsafe Duties 210
11.8.2 Features Designed to Enhance Safety and Comfort in Human–Robot Collaboration 211
11.9 Creating Collaborative Environments 212
11.9.1 Innovations that Enable Seamless Interaction Between Mobile Robots and Human Operators 212
11.9.2 Examples of Collaborative Robots (Cobots) and their Impact on Efficiency and Job Satisfaction 213
11.10 Challenges and Future Directions in Human–Robot Interaction (HRI) 215
11.11 Future Trends and Innovation in Human–Robot Interaction 215
References 219
Part 4: Specialized Applications and Innovations 221
12 Augmented Reality in Healthcare: Applications, Security, and Mobile Robotics Integration 223
S. Darwin, A. Rega and E. Fantin Irudaya Raj
12.1 Introduction 224
12.2 Profitable Benefits of AR in Education 226
12.2.1 Medical Field 226
12.2.2 Engineering Field 227
12.2.2.1 Confrontation Factors in Augmented Reality-Based Wireless Communication 228
12.3 Patients Home Care through AR 230
12.3.1 Healthcare Intervention Using Wearable AR 230
12.3.2 Rehabilitation Practices Using AR 233
12.4 Surgeries Using AR Technology 234
12.5 Services of AR in Healthcare 237
12.5.1 Monitoring and Guidance in Health Care 237
12.6 Challenges 238
12.7 AR’s Potential in the Medical Field 238
12.8 Conclusion 239
References 240
13 Enhancing Data Security, Sustainability, and Robotics Integration in IoT-Enabled Healthcare Systems 247
Manjunatha Badiger, Jose Alex Mathew, Sushma P. S., Sharathchandra N. R., Gurusiddayya Hiremath and Manjunatha E. C.
13.1 Introduction 248
13.1.1 Overview of IoT in Healthcare: Applications and Significance in Patient Care 248
13.1.2 The Intertwined Challenges of Data Security and Sustainability in IoT Healthcare Systems 250
13.1.3 Importance of Addressing these Issues for Enhancing System Reliability and Patient Outcomes 251
13.2 Data Security in IoT-Enabled Healthcare Systems 251
13.2.1 Common Vulnerabilities in IoT Healthcare 252
13.2.2 Regulatory Landscape and Compliance Requirements 253
13.2.3 Consequences of Security Lapses 254
13.3 Strategies for Enhancing Data Security 256
13.3.1 Advanced Encryption Standards and Secure Communication Protocols 256
13.3.2 Role of Blockchain in Ensuring Data Integrity and Traceability 256
13.3.3 Biometric and Multi-Factor Authentication Mechanisms 257
13.3.4 AI-Based Threat Detection and Response Systems 257
13.4 Robotics in IoT-Enabled Healthcare 258
13.4.1 Role of Robotics in Enhancing Healthcare Delivery and Patient Outcomes 259
13.4.2 Secure Integration of IoT and Robotic Systems for Real-Time Monitoring and Surgical Assistance 259
13.4.3 Energy-Efficient Designs for Robotic Healthcare Devices 260
13.4.4 Robotics and AI Synergy for Personalized and Autonomous Healthcare Solutions 260
13.5 Sustainability Challenges in IoT Healthcare Systems 261
13.5.1 Energy Demands of IoT Devices and their Impact on Sustainability 261
13.5.2 Environmental and Operational Implications of Inefficient Energy Management 262
13.5.3 Critical Need for Balancing Performance with Energy Consumption 263
13.6 Energy Efficiency in IoT Healthcare 263
13.6.1 Adoption of Low-Power Communication Protocols 263
13.6.2 Edge Computing to Minimize Energy-Intensive Cloud Communication 265
13.6.3 Energy-Harvesting Technologies for Device Longevity 265
13.6.4 Design Considerations for Creating Energy-Efficient IoT Networks 267
13.7 Case Study 268
13.7.1 Strengthening Cybersecurity for a Leading Private Hospital in London 269
13.7.2 Case Study: BP’s Integration of Wearables Into Employee Wellness Programs 270
13.8 Conclusion 271
References 271
14 Role of Blockchain and Mobile Robotics in Industry 5.0 – A Detailed Investigation 275
P. Gayathri, A. Ravi, E. Fantin Irudaya Raj and M. Appadurai
14.1 Introduction 276
14.2 Evolution of Industry 5.0 276
14.3 Portrayal of Block Chain 277
14.4 Architecture of IoT 278
14.5 STM and STC Chain in BC 279
14.6 Mobile Robotics Technologies 279
14.7 Mobile Robotics Views from A to Z 280
14.8 Risks in Industry 5.0 281
14.9 Cloud Solutions in Industry 5.0 283
14.10 Limitations for Industry 5.0 286
14.11 Control Approaches 286
14.12 Revised Remodels in Industry 5.0 288
14.13 Applications of Industry 5.0 289
14.14 Applications of BC 289
14.15 Upcoming Research for Industry 5.0 290
14.16 Future Developments for Industry 6.0 291
14.17 Conclusion 291
Bibliography 292
15 Sustainability and Resilience in Industry 5.0: Leveraging Machine Learning and AI Technologies 303
Dankan Gowda V., Nidadavolu Venkat D.S.S.V. Prasad Raju, Kottala Sri Yogi, Mandeep Kaur and Srinivas D.
15.1 Introduction 304
15.2 Conceptual Framework of Industry 5.0 306
15.3 Literature Survey 308
15.4 Machine Learning Techniques for Sustainability 310
15.5 AI Technologies Driving Resilience 312
15.6 Sustainable Supply Chain Management 315
15.7 Results and Discussion 317
15.8 Future Directions and Challenges 321
15.9 Conclusion 322
References 323
16 Development of an Auto Navigation Robot with LiDAR Technology 327
Shrividya G., Sushma P. S., Charan, Chirag Ballal, Chethan K. T., Deepak V. S. and Usha Desai
16.1 Introduction 328
16.2 Methodology 330
16.3 Design and Implementation 331
16.4 Results and Discussion 333
16.5 Conclusion 335
References 336
17 Design of Self-Sustaining Wall Projected Virtual Reality-Based Home and Industrial Automation System 339
J. Naga Vishnu Vardhan, G. Rama Lakshmi, G. R. L. V. N. Srinivasa Raju, P. Sindhu, T. Sai Deepika, Iffath Fathima, Prasanna Laxmi and Usha Desai
17.1 Introduction 340
17.2 Methodology 342
17.3 Results and Discussion 344
17.4 Conclusion 348
References 348
18 Review of Sensor Fusion Applications in Autonomous Vehicles 351
Aditya Avinash and Rathishchandra Ramachandra Gatti
18.1 Introduction 351
18.1.1 Challenges Faced by Sensors in AVs 352
18.2 Sensor Modalities in AVs 354
18.3 Sensor Calibration 359
18.4 Sensor Fusion Techniques 361
18.5 Applications and Case Studies 364
18.6 Challenges and Future Directions 368
18.7 Conclusion 370
References 371
19 Mobile Robotics in Industry 5.0: Leveraging AI and Machine Learning for Human-Centric Automation 375
Suchetha G., Harinakshi C., Masooda and Chinmai Shetty
19.1 Introduction to Industry 5.0 and Mobile Robotics 376
19.2 AI and ML Concepts Empower Mobile Robotics in Industry 5.0 381
19.3 Key AI Algorithms in Mobile Robotics 382
19.4 Core Technologies in Mobile Robotics for Industry 5.0 384
19.4.1 Natural Language Processing (NLP) and Voice Recognition: Facilitating Verbal Communication 384
19.5 Applications and Use Cases of Mobile Robotics in Industry 5.0 385
19.5.1 Collaborative Robotics on Production Floors 385
19.6 Technical Challenges and Limitations in Mobile Robotics for Industry 5.0 386
19.6.1 Data Processing and Real-Time Decision Making 386
19.7 Future Trends and Innovations in Mobile Robotics for Industry 5.0 387
19.8 Conclusion 388
References 389
About the Editors 391
Index 393
