Design and Optimization of Mobile Robotics for Industry 5.0

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.

Table of Contents:
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

About the Author :
Rathishchandra R. Gatti, PhD is the Dean of Research and Development and professor in the Departments of Mechanical Engineering and Robotics and Automation at the Sahyadri College of Engineering and Management with over 20 years of experience. He has published four patents, seven books, and more than 40 peer-reviewed publications. His research interests include robotics, AI in engineering, physical AI, and machine data analytics. Chandra Singh is an assistant professor in the Department of Electronics and Communication Engineering at Nitte University. He has published more than 35 articles and six patents, and edited ten books. His research interests include optical networking and communication, wireless communication, Internet of Things, and machine learning. Ajith B.S., PhD is an associate professor in the Department of Mechanical and Robotics Engineering and Associate Dean of Intellectual Property Rights at the Sahyadri College of Engineering and Management. He has published more than 18 journal papers, presented ten conference papers, authored many patents, and contributed to a number of books. His research focuses on biofuels, renewable energy, combustion, and heat transfer. E. Fantin Irudaya Raj, PhD is a professor of Electrical and Electronics Engineering at the Aditanar College of Engineering with over a decade of experience. He has published more than 35 journal publications, 50 conference papers, patents, and book contributions. His research interests include power electronic drives, Internet of Things, smart cities, image processing, and AI techniques.