Infrastructure Robotics
Methodologies, Robotic Systems and Applications
IEEE Series on Systems Science and Engineering
1. Edition December 2023
432 Pages, Hardcover
Wiley & Sons Ltd
ISBN:
978-1-394-16284-0
John Wiley & Sons
Infrastructure Robotics
Illuminating resource presenting commonly used robotic methodologies and technologies, with recent developments and clear application examples across different project types
Infrastructure Robotics presents state-of-the-art research in infrastructure robotics and key methodologies that enable the development of intelligent robots for operation in civil infrastructure environments, describing sensing, perception, localization, map building, environmental and operation awareness, motion and task planning, design methodologies, robot assistance paradigms, and physical human-robot collaboration. The text also presents many case studies of robotic systems developed for real-world applications in maintaining various civil infrastructures, including steel bridges, tunnels, underground water mains, underwater structures, and sewer pipes. In addition, later chapters discuss lessons learned in deployment of intelligent robots in practical applications overall.
Infrastructure Robotics provides a timely and thorough treatment of the subject pertaining to recent developments, such as computer vision and machine learning techniques that have been used in inspection and condition assessment of critical civil infrastructures, including bridges, tunnels, and more.
Written by highly qualified contributors with significant experience in both academia and industry, Infrastructure Robotics covers topics such as:
* Design methods for application of robots in civil infrastructure inspired by biological systems including ants, inchworms, and humans
* Fundamental aspects of research on intelligent robotic co-workers for human-robot collaborative operations
* The ROBO-SPECT European project and a robotized alternative to manual tunnel structural inspection and assessment
* Wider context for the use of additive manufacturing techniques on construction sites
Infrastructure Robotics is an essential resource for researchers, engineers, and graduate students in related fields. Professionals in civil engineering, asset management, and project management who wish to be on the cutting edge of the future of their industries will also benefit from the text.
About the Editors xv
Preface xix
Acronyms xxi
Part I Methodologies 1
1 Infrastructure Robotics: An Introduction 3
Dikai Liu and Gamini Dissanayake
1.1 Infrastructure Inspection and Maintenance 3
1.2 Infrastructure Robotics 6
1.2.1 Inspection and Maintenance of Steel Bridges 7
1.2.2 Climbing and Wheeled Robots for Inspection of Truss Structures 8
1.2.3 Robots for Underwater Infrastructure Maintenance 10
1.3 Considerations in Infrastructure Robotics Research 11
1.4 Opportunities and Challenges 13
1.5 Concluding Remarks 15
Bibliography 15
2 Design of Infrastructure Robotic Systems 19
Kenneth Waldron
2.1 Special Features of Infrastructure 19
2.2 The Design Process 20
2.3 Types of Robots and Their Design and Operation 21
2.4 Software System Design 23
2.5 An Example: Development of the CROC Design Concept 23
2.6 Some Other Examples 27
2.7 Actuator Systems 30
2.8 Concluding Remarks 31
Bibliography 31
3 Perception in Complex and Unstructured Infrastructure Environments 33
Shoudong Huang, Kai Pan, and Gamini Dissanayake
3.1 Introduction 33
3.2 Sensor Description 35
3.2.1 2D LiDAR 35
3.2.2 3D LiDAR 35
3.2.3 Sonar 36
3.2.4 Monocular Camera 36
3.2.5 Stereo Camera 36
3.2.6 GRB-D Camera 37
3.3 Problem Description 37
3.4 Theoretical Foundations 38
3.4.1 Extended Kalman Filter 39
3.4.2 Nonlinear Least Squares 40
3.4.3 Environment Representations 42
3.4.4 Mapping Techniques 44
3.4.5 Localization Techniques 47
3.4.6 SLAM Techniques 49
3.5 Implementation 53
3.5.1 Localization 54
3.5.2 Slam 54
3.6 Case Studies 55
3.6.1 Mapping in Confined Space 55
3.6.2 Localization in Confined Space 55
3.6.3 SLAM in Underwater Bridge Environment 56
3.7 Conclusion and Discussion 56
Bibliography 57
4 Machine Learning and Computer Vision Applications in Civil Infrastructure Inspection and Monitoring 59
Shuming Liang, Andy Guo, Bin Liang, Zhidong Li, Yu Ding, Yang Wang, and Fang Chen
4.1 Introduction 59
4.2 GNN-Based Pipe Failure Prediction 60
4.2.1 Background 60
4.2.2 Problem Formulation 61
4.2.3 Data Preprocessing 61
4.2.4 GNN Learning 62
4.2.5 Failure Pattern Learning 64
4.2.6 Failure Predictor 65
4.2.7 Experimental Study 65
4.3 Computer Vision-Based Signal Aspect Transition Detection 67
4.3.1 Background 67
4.3.2 Signal Detection Model 67
4.3.3 Track Detection Model 69
4.3.4 Optimization for Target Locating 72
4.4 Conclusion and Discussion 75
Bibliography 77
5 Coverage Planning and Motion Planning of Intelligent Robots for Civil Infrastructure Maintenance 81
Mahdi Hassan and Dikai Liu
5.1 Introduction to Coverage and Motion Planning 81
5.2 Coverage Planning Algorithms for a Single Robot 82
5.2.1 An Offline Coverage Planning Algorithm 82
5.2.2 A Real-Time Coverage Planning Algorithm 86
5.3 Coverage Planning Algorithms for Multiple Robots 90
5.3.1 Base Placement Optimization 90
5.3.2 Area Partitioning and Allocation 93
5.3.3 Adaptive Coverage Path Planning 97
5.4 Conclusion 101
Bibliography 102
6 Methodologies in Physical Human-Robot Collaboration for Infrastructure Maintenance 105
Marc G. Carmichael, Antony Tran, Stefano Aldini, and Dikai Liu
6.1 Introduction 105
6.2 Autonomy, Tele-Operation, and pHRC 106
6.2.1 Autonomous Robots 106
6.2.2 Teleoperated Robots 108
6.2.3 Physical Human-Robot Collaboration 109
6.3 Control Methods 110
6.3.1 Motion Control 110
6.3.2 Force Control 111
6.4 Adaptive Assistance Paradigms 113
6.4.1 Manually Adapted Assistance 114
6.4.2 Assistance-As-Needed Paradigms 115
6.4.3 Performance-Based Assistance 115
6.4.4 Physiology-Based Assistance 116
6.5 Safety Framework for pHRC 117
6.6 Performance-Based Role Change 119
6.7 Case Study 121
6.8 Discussion 122
Acknowledgements 123
Bibliography 123
Part II Robotic System Design and Applications 127
7 Steel Bridge Climbing Robot Design and Development 129
Hung M. La
7.1 Introduction 129
7.2 Recent Climbing Robot Platforms Developed by the ARA Lab 133
7.3 Overall Design 134
7.3.1 Mechanical Design and Analysis 136
7.4 Overall Control Architecture 140
7.4.1 Control System Framework 141
7.5 Experiment Results 148
7.5.1 Switching Control 149
7.5.2 Robot Navigation in Mobile and Worming Transformation 152
7.5.3 Robot Deployment 153
7.6 Conclusion and Future Work 155
Bibliography 156
8 Underwater Robots for Cleaning and Inspection of Underwater Structures 161
Andrew Wing Keung To, Khoa Le, and Dikai Liu
8.1 Introduction to Maintenance of Underwater Structures 161
8.2 Robot System Design 163
8.2.1 Hull Design and Maneuvering System 164
8.2.2 Robot Arms for Docking and Water-Jet Cleaning 164
8.3 Sensing and Perception in Underwater Environments 166
8.3.1 Underwater Simultaneous Localization and Mapping (SLAM) Around Bridge Piles 167
8.3.2 Marine Growth Identification 168
8.4 Software Architecture 170
8.5 Robot Navigation, Motion Planning and System Integration 170
8.5.1 Localization and Navigation in Open Water 170
8.5.2 System Integration 173
8.6 Testing in a Lab Setup and Trials in the Field 174
8.6.1 Operation Procedure 174
8.6.2 Autonomous Navigation in Narrow Environments 176
8.6.3 Vision-Based Marine Growth Removing Process 178
8.6.4 Inspection and Marine Growth Identification 179
8.7 Reflection and Lessons Learned 180
8.8 Conclusion and Future Work 181
Acknowledgments 182
Bibliography 182
9 Tunnel Structural Inspection and Assessment Using an Autonomous Robotic System 185
Juan G. Victores, E. Menendez, and C. Balaguer
9.1 Introduction 185
9.2 ROBO-SPECT Project 186
9.2.1 Robotic System 187
9.2.2 Intelligent Global Controller 191
9.2.3 Ground Control Station 192
9.2.4 Structural Assessment Tool 192
9.3 Inspection Procedure 192
9.4 Extended Kalman Filter for Mobile Vehicle Localization 195
9.5 Mobile Vehicle Navigation 197
9.6 Field Experimental Results 198
9.7 Conclusion 201
Bibliography 201
10 BADGER: Intelligent Robotic System for Underground Construction 205
Santiago Martínez, Marcos Marín, Elisabeth Menéndez, Panagiotis Vartholomeos, Dimitrios Giakoumis, Alessandro Simi, and Carlos Balaguer
10.1 Introduction 205
10.2 Boring Systems and Methods 207
10.2.1 Directional Drilling Methods 207
10.2.2 Drilling Robotic Systems 209
10.3 Main Drawbacks 210
10.4 BADGER System and Components 212
10.4.1 Main Systems Description 212
10.4.2 BADGER Operation 215
10.5 Future Trends 218
Bibliography 218
11 Robots for Underground Pipe Condition Assessment 221
Jaime Valls Miro
11.1 Introduction to Ferro-Magnetic Pipeline Maintenance 221
11.1.1 NDT Inspection Taxonomy 222
11.2 Inspection Robots 223
11.2.1 Robot Kinematics and Locomotion 224
11.3 PEC Sensing for Ferromagnetic Wall Thickness Mapping 228
11.3.1 Hardware and Software System Architecture 230
11.4 Gaussian Processes for Spatial Regression from Sampled Inspection Data 232
11.4.1 Gaussian Processes 234
11.5 Field Robotic CA Inspection Results 236
11.6 Concluding Remarks 240
Bibliography 240
12 Robotics and Sensing for Condition Assessment of Wastewater Pipes 243
Sarath Kodagoda, Vinoth Kumar Viswanathan, Karthick Thiyagarajan, Antony Tran, Sathira Wickramanayake, Steve Barclay, and Dammika Vitanage
12.1 Introduction 243
12.2 Nondestructive Sensing System for Condition Assessment of Sewer Walls 245
12.3 Robotic Tool for Field Deployment 252
12.4 Laboratory Evaluation 254
12.5 Field Deployment and Evaluation 255
12.6 Lessons Learned and Future Directions 258
12.7 Concluding Remarks 259
Bibliography 260
13 A Climbing Robot for Maintenance Operations in Confined Spaces 263
Gibson Hu, Dinh Dang Khoa Le, and Dikai Liu
13.1 Introduction 263
13.2 Robot Design 265
13.3 Methodologies 271
13.3.1 Perception 271
13.3.2 Control 274
13.3.3 Planning of Robot Body Motion 279
13.4 Experiments and Results 279
13.4.1 Experiment Setup 279
13.4.2 Lab Test Results 280
13.4.3 Field Trials in a Steel Bridge 282
13.5 Discussion 283
13.6 Conclusion 283
Bibliography 284
14 Multi-UAV Systems for Inspection of Industrial and Public Infrastructures 285
Alvaro Caballero, Julio L. Paneque, Jose R. Martinez-de-Dios, Ivan Maza, and Anibal Ollero
14.1 Introduction 285
14.2 Multi-UAV Inspection of Electrical Power Systems 287
14.2.1 Use Cases 287
14.2.2 Architecture 288
14.3 Inspection Planning 289
14.3.1 Vehicle Routing Problem 289
14.4 Onboard Online Semantic Mapping 296
14.4.1 GNSS-Endowed Mapping System 296
14.4.2 Reflectivity and Geometry-Based Semantic Classification 297
14.4.3 Validation 298
14.5 Conclusion 300
Bibliography 302
15 Robotic Platforms for Inspection of Oil Refineries 305
Mauricio Calva
15.1 Refining Oil for Fuels and Petrochemical Basics 305
15.2 The Inspection Process 307
15.3 Inspection and Mechanical Integrity of Oil Refinery Components 310
15.3.1 Liquid Storage Tank Inspection 310
15.3.2 Pressurized Vessels Inspection 312
15.3.3 Process Pipping 314
15.3.4 Heat Exchanger Bundles 315
15.4 Plant Operations, Surveillance, Maintenance Activities, and Others 316
15.4.1 Surveillance, Operations, and Maintenance of Oil and Gas Refineries 316
15.4.2 Safety and Security 318
15.4.3 Utilities and Support Activities 318
15.5 Robotic Systems for Inspection 319
15.5.1 Robotics for Storage Tanks 320
15.5.2 Robotics for Pressure Vessels 324
15.5.3 Robotics for Process Piping 328
15.5.4 Robotics Heat Exchanger Bundles 331
15.6 Robotics for Plant Operations, Surveillance, Maintenance, and Other Related Activities 332
15.6.1 Operations, Surveillance, and Maintenance of Oil and Gas Refineries with Robotic Systems 332
15.6.2 Safety and Security Robotics 334
15.6.3 Robotics for Utilities and Support Activities 335
15.7 Conclusion 335
16 Drone-Based Solar Cell Inspection With Autonomous Deep Learning 337
Zhounan Wang, Peter Zheng, Basaran Bahadir Kocer, and Mirko Kovac
16.1 Introduction 337
16.1.1 Motivation 337
16.1.2 Related Works 339
16.1.3 Scope 341
16.2 Aerial Robot and Detection Framework 341
16.2.1 Simulation Environment 343
16.2.2 Solar Panel Detection 343
16.2.3 Aerial Robot Trajectory 345
16.2.4 Sensory Instrumentation for Aerial Robot 346
16.3 Learning Framework 348
16.3.1 Dataset Preparation 349
16.3.2 CNN Architecture 351
16.3.3 Performance Evaluation Measures 352
16.4 Conclusion 357
Acknowledgments 358
Bibliography 358
17 Aerial Repair and Aerial Additive Manufacturing 367
Yusuf Furkan Kaya, Lachlan Orr, Basaran Bahadir Kocer, and Mirko Kovac
17.1 Review of State of the Art in Additive Manufacturing at Architectural Scales 367
17.2 Review of Demonstrations of Aerial Manufacturing and Repair 371
17.2.1 Demands and Challenges 374
17.2.2 Future Prospects 376
17.3 Initial Experimental Evaluations 378
17.4 Conclusion and Discussion 379
Bibliography 379
Index 385
Preface xix
Acronyms xxi
Part I Methodologies 1
1 Infrastructure Robotics: An Introduction 3
Dikai Liu and Gamini Dissanayake
1.1 Infrastructure Inspection and Maintenance 3
1.2 Infrastructure Robotics 6
1.2.1 Inspection and Maintenance of Steel Bridges 7
1.2.2 Climbing and Wheeled Robots for Inspection of Truss Structures 8
1.2.3 Robots for Underwater Infrastructure Maintenance 10
1.3 Considerations in Infrastructure Robotics Research 11
1.4 Opportunities and Challenges 13
1.5 Concluding Remarks 15
Bibliography 15
2 Design of Infrastructure Robotic Systems 19
Kenneth Waldron
2.1 Special Features of Infrastructure 19
2.2 The Design Process 20
2.3 Types of Robots and Their Design and Operation 21
2.4 Software System Design 23
2.5 An Example: Development of the CROC Design Concept 23
2.6 Some Other Examples 27
2.7 Actuator Systems 30
2.8 Concluding Remarks 31
Bibliography 31
3 Perception in Complex and Unstructured Infrastructure Environments 33
Shoudong Huang, Kai Pan, and Gamini Dissanayake
3.1 Introduction 33
3.2 Sensor Description 35
3.2.1 2D LiDAR 35
3.2.2 3D LiDAR 35
3.2.3 Sonar 36
3.2.4 Monocular Camera 36
3.2.5 Stereo Camera 36
3.2.6 GRB-D Camera 37
3.3 Problem Description 37
3.4 Theoretical Foundations 38
3.4.1 Extended Kalman Filter 39
3.4.2 Nonlinear Least Squares 40
3.4.3 Environment Representations 42
3.4.4 Mapping Techniques 44
3.4.5 Localization Techniques 47
3.4.6 SLAM Techniques 49
3.5 Implementation 53
3.5.1 Localization 54
3.5.2 Slam 54
3.6 Case Studies 55
3.6.1 Mapping in Confined Space 55
3.6.2 Localization in Confined Space 55
3.6.3 SLAM in Underwater Bridge Environment 56
3.7 Conclusion and Discussion 56
Bibliography 57
4 Machine Learning and Computer Vision Applications in Civil Infrastructure Inspection and Monitoring 59
Shuming Liang, Andy Guo, Bin Liang, Zhidong Li, Yu Ding, Yang Wang, and Fang Chen
4.1 Introduction 59
4.2 GNN-Based Pipe Failure Prediction 60
4.2.1 Background 60
4.2.2 Problem Formulation 61
4.2.3 Data Preprocessing 61
4.2.4 GNN Learning 62
4.2.5 Failure Pattern Learning 64
4.2.6 Failure Predictor 65
4.2.7 Experimental Study 65
4.3 Computer Vision-Based Signal Aspect Transition Detection 67
4.3.1 Background 67
4.3.2 Signal Detection Model 67
4.3.3 Track Detection Model 69
4.3.4 Optimization for Target Locating 72
4.4 Conclusion and Discussion 75
Bibliography 77
5 Coverage Planning and Motion Planning of Intelligent Robots for Civil Infrastructure Maintenance 81
Mahdi Hassan and Dikai Liu
5.1 Introduction to Coverage and Motion Planning 81
5.2 Coverage Planning Algorithms for a Single Robot 82
5.2.1 An Offline Coverage Planning Algorithm 82
5.2.2 A Real-Time Coverage Planning Algorithm 86
5.3 Coverage Planning Algorithms for Multiple Robots 90
5.3.1 Base Placement Optimization 90
5.3.2 Area Partitioning and Allocation 93
5.3.3 Adaptive Coverage Path Planning 97
5.4 Conclusion 101
Bibliography 102
6 Methodologies in Physical Human-Robot Collaboration for Infrastructure Maintenance 105
Marc G. Carmichael, Antony Tran, Stefano Aldini, and Dikai Liu
6.1 Introduction 105
6.2 Autonomy, Tele-Operation, and pHRC 106
6.2.1 Autonomous Robots 106
6.2.2 Teleoperated Robots 108
6.2.3 Physical Human-Robot Collaboration 109
6.3 Control Methods 110
6.3.1 Motion Control 110
6.3.2 Force Control 111
6.4 Adaptive Assistance Paradigms 113
6.4.1 Manually Adapted Assistance 114
6.4.2 Assistance-As-Needed Paradigms 115
6.4.3 Performance-Based Assistance 115
6.4.4 Physiology-Based Assistance 116
6.5 Safety Framework for pHRC 117
6.6 Performance-Based Role Change 119
6.7 Case Study 121
6.8 Discussion 122
Acknowledgements 123
Bibliography 123
Part II Robotic System Design and Applications 127
7 Steel Bridge Climbing Robot Design and Development 129
Hung M. La
7.1 Introduction 129
7.2 Recent Climbing Robot Platforms Developed by the ARA Lab 133
7.3 Overall Design 134
7.3.1 Mechanical Design and Analysis 136
7.4 Overall Control Architecture 140
7.4.1 Control System Framework 141
7.5 Experiment Results 148
7.5.1 Switching Control 149
7.5.2 Robot Navigation in Mobile and Worming Transformation 152
7.5.3 Robot Deployment 153
7.6 Conclusion and Future Work 155
Bibliography 156
8 Underwater Robots for Cleaning and Inspection of Underwater Structures 161
Andrew Wing Keung To, Khoa Le, and Dikai Liu
8.1 Introduction to Maintenance of Underwater Structures 161
8.2 Robot System Design 163
8.2.1 Hull Design and Maneuvering System 164
8.2.2 Robot Arms for Docking and Water-Jet Cleaning 164
8.3 Sensing and Perception in Underwater Environments 166
8.3.1 Underwater Simultaneous Localization and Mapping (SLAM) Around Bridge Piles 167
8.3.2 Marine Growth Identification 168
8.4 Software Architecture 170
8.5 Robot Navigation, Motion Planning and System Integration 170
8.5.1 Localization and Navigation in Open Water 170
8.5.2 System Integration 173
8.6 Testing in a Lab Setup and Trials in the Field 174
8.6.1 Operation Procedure 174
8.6.2 Autonomous Navigation in Narrow Environments 176
8.6.3 Vision-Based Marine Growth Removing Process 178
8.6.4 Inspection and Marine Growth Identification 179
8.7 Reflection and Lessons Learned 180
8.8 Conclusion and Future Work 181
Acknowledgments 182
Bibliography 182
9 Tunnel Structural Inspection and Assessment Using an Autonomous Robotic System 185
Juan G. Victores, E. Menendez, and C. Balaguer
9.1 Introduction 185
9.2 ROBO-SPECT Project 186
9.2.1 Robotic System 187
9.2.2 Intelligent Global Controller 191
9.2.3 Ground Control Station 192
9.2.4 Structural Assessment Tool 192
9.3 Inspection Procedure 192
9.4 Extended Kalman Filter for Mobile Vehicle Localization 195
9.5 Mobile Vehicle Navigation 197
9.6 Field Experimental Results 198
9.7 Conclusion 201
Bibliography 201
10 BADGER: Intelligent Robotic System for Underground Construction 205
Santiago Martínez, Marcos Marín, Elisabeth Menéndez, Panagiotis Vartholomeos, Dimitrios Giakoumis, Alessandro Simi, and Carlos Balaguer
10.1 Introduction 205
10.2 Boring Systems and Methods 207
10.2.1 Directional Drilling Methods 207
10.2.2 Drilling Robotic Systems 209
10.3 Main Drawbacks 210
10.4 BADGER System and Components 212
10.4.1 Main Systems Description 212
10.4.2 BADGER Operation 215
10.5 Future Trends 218
Bibliography 218
11 Robots for Underground Pipe Condition Assessment 221
Jaime Valls Miro
11.1 Introduction to Ferro-Magnetic Pipeline Maintenance 221
11.1.1 NDT Inspection Taxonomy 222
11.2 Inspection Robots 223
11.2.1 Robot Kinematics and Locomotion 224
11.3 PEC Sensing for Ferromagnetic Wall Thickness Mapping 228
11.3.1 Hardware and Software System Architecture 230
11.4 Gaussian Processes for Spatial Regression from Sampled Inspection Data 232
11.4.1 Gaussian Processes 234
11.5 Field Robotic CA Inspection Results 236
11.6 Concluding Remarks 240
Bibliography 240
12 Robotics and Sensing for Condition Assessment of Wastewater Pipes 243
Sarath Kodagoda, Vinoth Kumar Viswanathan, Karthick Thiyagarajan, Antony Tran, Sathira Wickramanayake, Steve Barclay, and Dammika Vitanage
12.1 Introduction 243
12.2 Nondestructive Sensing System for Condition Assessment of Sewer Walls 245
12.3 Robotic Tool for Field Deployment 252
12.4 Laboratory Evaluation 254
12.5 Field Deployment and Evaluation 255
12.6 Lessons Learned and Future Directions 258
12.7 Concluding Remarks 259
Bibliography 260
13 A Climbing Robot for Maintenance Operations in Confined Spaces 263
Gibson Hu, Dinh Dang Khoa Le, and Dikai Liu
13.1 Introduction 263
13.2 Robot Design 265
13.3 Methodologies 271
13.3.1 Perception 271
13.3.2 Control 274
13.3.3 Planning of Robot Body Motion 279
13.4 Experiments and Results 279
13.4.1 Experiment Setup 279
13.4.2 Lab Test Results 280
13.4.3 Field Trials in a Steel Bridge 282
13.5 Discussion 283
13.6 Conclusion 283
Bibliography 284
14 Multi-UAV Systems for Inspection of Industrial and Public Infrastructures 285
Alvaro Caballero, Julio L. Paneque, Jose R. Martinez-de-Dios, Ivan Maza, and Anibal Ollero
14.1 Introduction 285
14.2 Multi-UAV Inspection of Electrical Power Systems 287
14.2.1 Use Cases 287
14.2.2 Architecture 288
14.3 Inspection Planning 289
14.3.1 Vehicle Routing Problem 289
14.4 Onboard Online Semantic Mapping 296
14.4.1 GNSS-Endowed Mapping System 296
14.4.2 Reflectivity and Geometry-Based Semantic Classification 297
14.4.3 Validation 298
14.5 Conclusion 300
Bibliography 302
15 Robotic Platforms for Inspection of Oil Refineries 305
Mauricio Calva
15.1 Refining Oil for Fuels and Petrochemical Basics 305
15.2 The Inspection Process 307
15.3 Inspection and Mechanical Integrity of Oil Refinery Components 310
15.3.1 Liquid Storage Tank Inspection 310
15.3.2 Pressurized Vessels Inspection 312
15.3.3 Process Pipping 314
15.3.4 Heat Exchanger Bundles 315
15.4 Plant Operations, Surveillance, Maintenance Activities, and Others 316
15.4.1 Surveillance, Operations, and Maintenance of Oil and Gas Refineries 316
15.4.2 Safety and Security 318
15.4.3 Utilities and Support Activities 318
15.5 Robotic Systems for Inspection 319
15.5.1 Robotics for Storage Tanks 320
15.5.2 Robotics for Pressure Vessels 324
15.5.3 Robotics for Process Piping 328
15.5.4 Robotics Heat Exchanger Bundles 331
15.6 Robotics for Plant Operations, Surveillance, Maintenance, and Other Related Activities 332
15.6.1 Operations, Surveillance, and Maintenance of Oil and Gas Refineries with Robotic Systems 332
15.6.2 Safety and Security Robotics 334
15.6.3 Robotics for Utilities and Support Activities 335
15.7 Conclusion 335
16 Drone-Based Solar Cell Inspection With Autonomous Deep Learning 337
Zhounan Wang, Peter Zheng, Basaran Bahadir Kocer, and Mirko Kovac
16.1 Introduction 337
16.1.1 Motivation 337
16.1.2 Related Works 339
16.1.3 Scope 341
16.2 Aerial Robot and Detection Framework 341
16.2.1 Simulation Environment 343
16.2.2 Solar Panel Detection 343
16.2.3 Aerial Robot Trajectory 345
16.2.4 Sensory Instrumentation for Aerial Robot 346
16.3 Learning Framework 348
16.3.1 Dataset Preparation 349
16.3.2 CNN Architecture 351
16.3.3 Performance Evaluation Measures 352
16.4 Conclusion 357
Acknowledgments 358
Bibliography 358
17 Aerial Repair and Aerial Additive Manufacturing 367
Yusuf Furkan Kaya, Lachlan Orr, Basaran Bahadir Kocer, and Mirko Kovac
17.1 Review of State of the Art in Additive Manufacturing at Architectural Scales 367
17.2 Review of Demonstrations of Aerial Manufacturing and Repair 371
17.2.1 Demands and Challenges 374
17.2.2 Future Prospects 376
17.3 Initial Experimental Evaluations 378
17.4 Conclusion and Discussion 379
Bibliography 379
Index 385
DIKAI LIU, PHD, is a Distinguished Professor at the University of Technology Sydney.
CARLOS BALAGUER, PHD, is a Full Professor at University Carlos III of Madrid (UC3M).
GAMINI DISSANAYAKE, PHD, is an Emeritus Professor at the University of Technology Sydney.
MIRKO KOVAC, PHD, is Director of the Aerial Robotics Laboratory at Imperial College London and the Head of the Laboratory of Sustainability Robotics at the Swiss Federal Laboratories for Material Science and Technology (Empa).
CARLOS BALAGUER, PHD, is a Full Professor at University Carlos III of Madrid (UC3M).
GAMINI DISSANAYAKE, PHD, is an Emeritus Professor at the University of Technology Sydney.
MIRKO KOVAC, PHD, is Director of the Aerial Robotics Laboratory at Imperial College London and the Head of the Laboratory of Sustainability Robotics at the Swiss Federal Laboratories for Material Science and Technology (Empa).
