Infrastructure Robotics

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).

• About the Editors xvPreface xixAcronyms xxiPart I Methodologies 11 Infrastructure Robotics: An Introduction 3Dikai Liu and Gamini Dissanayake1.1 Infrastructure Inspection and Maintenance 31.2 Infrastructure Robotics 61.2.1 Inspection and Maintenance of Steel Bridges 71.2.2 Climbing and Wheeled Robots for Inspection of Truss Structures 81.2.3 Robots for Underwater Infrastructure Maintenance 101.3 Considerations in Infrastructure Robotics Research 111.4 Opportunities and Challenges 131.5 Concluding Remarks 15Bibliography 152 Design of Infrastructure Robotic Systems 19Kenneth Waldron2.1 Special Features of Infrastructure 192.2 The Design Process 202.3 Types of Robots and Their Design and Operation 212.4 Software System Design 232.5 An Example: Development of the CROC Design Concept 232.6 Some Other Examples 272.7 Actuator Systems 302.8 Concluding Remarks 31Bibliography 313 Perception in Complex and Unstructured Infrastructure Environments 33Shoudong Huang, Kai Pan, and Gamini Dissanayake3.1 Introduction 333.2 Sensor Description 353.2.1 2D LiDAR 353.2.2 3D LiDAR 353.2.3 Sonar 363.2.4 Monocular Camera 363.2.5 Stereo Camera 363.2.6 GRB-D Camera 373.3 Problem Description 373.4 Theoretical Foundations 383.4.1 Extended Kalman Filter 393.4.2 Nonlinear Least Squares 403.4.3 Environment Representations 423.4.4 Mapping Techniques 443.4.5 Localization Techniques 473.4.6 SLAM Techniques 493.5 Implementation 533.5.1 Localization 543.5.2 Slam 543.6 Case Studies 553.6.1 Mapping in Confined Space 553.6.2 Localization in Confined Space 553.6.3 SLAM in Underwater Bridge Environment 563.7 Conclusion and Discussion 56Bibliography 574 Machine Learning and Computer Vision Applications in Civil Infrastructure Inspection and Monitoring 59Shuming Liang, Andy Guo, Bin Liang, Zhidong Li, Yu Ding, Yang Wang, and Fang Chen4.1 Introduction 594.2 GNN-Based Pipe Failure Prediction 604.2.1 Background 604.2.2 Problem Formulation 614.2.3 Data Preprocessing 614.2.4 GNN Learning 624.2.5 Failure Pattern Learning 644.2.6 Failure Predictor 654.2.7 Experimental Study 654.3 Computer Vision-Based Signal Aspect Transition Detection 674.3.1 Background 674.3.2 Signal Detection Model 674.3.3 Track Detection Model 694.3.4 Optimization for Target Locating 724.4 Conclusion and Discussion 75Bibliography 775 Coverage Planning and Motion Planning of Intelligent Robots for Civil Infrastructure Maintenance 81Mahdi Hassan and Dikai Liu5.1 Introduction to Coverage and Motion Planning 815.2 Coverage Planning Algorithms for a Single Robot 825.2.1 An Offline Coverage Planning Algorithm 825.2.2 A Real-Time Coverage Planning Algorithm 865.3 Coverage Planning Algorithms for Multiple Robots 905.3.1 Base Placement Optimization 905.3.2 Area Partitioning and Allocation 935.3.3 Adaptive Coverage Path Planning 975.4 Conclusion 101Bibliography 1026 Methodologies in Physical Human–Robot Collaboration for Infrastructure Maintenance 105Marc G. Carmichael, Antony Tran, Stefano Aldini, and Dikai Liu6.1 Introduction 1056.2 Autonomy, Tele-Operation, and pHRC 1066.2.1 Autonomous Robots 1066.2.2 Teleoperated Robots 1086.2.3 Physical Human–Robot Collaboration 1096.3 Control Methods 1106.3.1 Motion Control 1106.3.2 Force Control 1116.4 Adaptive Assistance Paradigms 1136.4.1 Manually Adapted Assistance 1146.4.2 Assistance-As-Needed Paradigms 1156.4.3 Performance-Based Assistance 1156.4.4 Physiology-Based Assistance 1166.5 Safety Framework for pHRC 1176.6 Performance-Based Role Change 1196.7 Case Study 1216.8 Discussion 122Acknowledgements 123Bibliography 123Part II Robotic System Design and Applications 1277 Steel Bridge Climbing Robot Design and Development 129Hung M. La7.1 Introduction 1297.2 Recent Climbing Robot Platforms Developed by the ARA Lab 1337.3 Overall Design 1347.3.1 Mechanical Design and Analysis 1367.4 Overall Control Architecture 1407.4.1 Control System Framework 1417.5 Experiment Results 1487.5.1 Switching Control 1497.5.2 Robot Navigation in Mobile and Worming Transformation 1527.5.3 Robot Deployment 1537.6 Conclusion and Future Work 155Bibliography 1568 Underwater Robots for Cleaning and Inspection of Underwater Structures 161Andrew Wing Keung To, Khoa Le, and Dikai Liu8.1 Introduction to Maintenance of Underwater Structures 1618.2 Robot System Design 1638.2.1 Hull Design and Maneuvering System 1648.2.2 Robot Arms for Docking and Water-Jet Cleaning 1648.3 Sensing and Perception in Underwater Environments 1668.3.1 Underwater Simultaneous Localization and Mapping (SLAM) Around Bridge Piles 1678.3.2 Marine Growth Identification 1688.4 Software Architecture 1708.5 Robot Navigation, Motion Planning and System Integration 1708.5.1 Localization and Navigation in Open Water 1708.5.2 System Integration 1738.6 Testing in a Lab Setup and Trials in the Field 1748.6.1 Operation Procedure 1748.6.2 Autonomous Navigation in Narrow Environments 1768.6.3 Vision-Based Marine Growth Removing Process 1788.6.4 Inspection and Marine Growth Identification 1798.7 Reflection and Lessons Learned 1808.8 Conclusion and Future Work 181Acknowledgments 182Bibliography 1829 Tunnel Structural Inspection and Assessment Using an Autonomous Robotic System 185Juan G. Victores, E. Menendez, and C. Balaguer9.1 Introduction 1859.2 ROBO-SPECT Project 1869.2.1 Robotic System 1879.2.2 Intelligent Global Controller 1919.2.3 Ground Control Station 1929.2.4 Structural Assessment Tool 1929.3 Inspection Procedure 1929.4 Extended Kalman Filter for Mobile Vehicle Localization 1959.5 Mobile Vehicle Navigation 1979.6 Field Experimental Results 1989.7 Conclusion 201Bibliography 20110 BADGER: Intelligent Robotic System for Underground Construction 205Santiago Martínez, Marcos Marín, Elisabeth Menéndez, Panagiotis Vartholomeos, Dimitrios Giakoumis, Alessandro Simi, and Carlos Balaguer10.1 Introduction 20510.2 Boring Systems and Methods 20710.2.1 Directional Drilling Methods 20710.2.2 Drilling Robotic Systems 20910.3 Main Drawbacks 21010.4 BADGER System and Components 21210.4.1 Main Systems Description 21210.4.2 BADGER Operation 21510.5 Future Trends 218Bibliography 21811 Robots for Underground Pipe Condition Assessment 221Jaime Valls Miro11.1 Introduction to Ferro-Magnetic Pipeline Maintenance 22111.1.1 NDT Inspection Taxonomy 22211.2 Inspection Robots 22311.2.1 Robot Kinematics and Locomotion 22411.3 PEC Sensing for Ferromagnetic Wall Thickness Mapping 22811.3.1 Hardware and Software System Architecture 23011.4 Gaussian Processes for Spatial Regression from Sampled Inspection Data 23211.4.1 Gaussian Processes 23411.5 Field Robotic CA Inspection Results 23611.6 Concluding Remarks 240Bibliography 24012 Robotics and Sensing for Condition Assessment of Wastewater Pipes 243Sarath Kodagoda, Vinoth Kumar Viswanathan, Karthick Thiyagarajan, Antony Tran, Sathira Wickramanayake, Steve Barclay, and Dammika Vitanage12.1 Introduction 24312.2 Nondestructive Sensing System for Condition Assessment of Sewer Walls 24512.3 Robotic Tool for Field Deployment 25212.4 Laboratory Evaluation 25412.5 Field Deployment and Evaluation 25512.6 Lessons Learned and Future Directions 25812.7 Concluding Remarks 259Bibliography 26013 A Climbing Robot for Maintenance Operations in Confined Spaces 263Gibson Hu, Dinh Dang Khoa Le, and Dikai Liu13.1 Introduction 26313.2 Robot Design 26513.3 Methodologies 27113.3.1 Perception 27113.3.2 Control 27413.3.3 Planning of Robot Body Motion 27913.4 Experiments and Results 27913.4.1 Experiment Setup 27913.4.2 Lab Test Results 28013.4.3 Field Trials in a Steel Bridge 28213.5 Discussion 28313.6 Conclusion 283Bibliography 28414 Multi-UAV Systems for Inspection of Industrial and Public Infrastructures 285Alvaro Caballero, Julio L. Paneque, Jose R. Martinez-de-Dios, Ivan Maza, and Anibal Ollero14.1 Introduction 28514.2 Multi-UAV Inspection of Electrical Power Systems 28714.2.1 Use Cases 28714.2.2 Architecture 28814.3 Inspection Planning 28914.3.1 Vehicle Routing Problem 28914.4 Onboard Online Semantic Mapping 29614.4.1 GNSS-Endowed Mapping System 29614.4.2 Reflectivity and Geometry-Based Semantic Classification 29714.4.3 Validation 29814.5 Conclusion 300Bibliography 30215 Robotic Platforms for Inspection of Oil Refineries 305Mauricio Calva15.1 Refining Oil for Fuels and Petrochemical Basics 30515.2 The Inspection Process 30715.3 Inspection and Mechanical Integrity of Oil Refinery Components 31015.3.1 Liquid Storage Tank Inspection 31015.3.2 Pressurized Vessels Inspection 31215.3.3 Process Pipping 31415.3.4 Heat Exchanger Bundles 31515.4 Plant Operations, Surveillance, Maintenance Activities, and Others 31615.4.1 Surveillance, Operations, and Maintenance of Oil and Gas Refineries 31615.4.2 Safety and Security 31815.4.3 Utilities and Support Activities 31815.5 Robotic Systems for Inspection 31915.5.1 Robotics for Storage Tanks 32015.5.2 Robotics for Pressure Vessels 32415.5.3 Robotics for Process Piping 32815.5.4 Robotics Heat Exchanger Bundles 33115.6 Robotics for Plant Operations, Surveillance, Maintenance, and Other Related Activities 33215.6.1 Operations, Surveillance, and Maintenance of Oil and Gas Refineries with Robotic Systems 33215.6.2 Safety and Security Robotics 33415.6.3 Robotics for Utilities and Support Activities 33515.7 Conclusion 33516 Drone-Based Solar Cell Inspection With Autonomous Deep Learning 337Zhounan Wang, Peter Zheng, Basaran Bahadir Kocer, and Mirko Kovac16.1 Introduction 33716.1.1 Motivation 33716.1.2 Related Works 33916.1.3 Scope 34116.2 Aerial Robot and Detection Framework 34116.2.1 Simulation Environment 34316.2.2 Solar Panel Detection 34316.2.3 Aerial Robot Trajectory 34516.2.4 Sensory Instrumentation for Aerial Robot 34616.3 Learning Framework 34816.3.1 Dataset Preparation 34916.3.2 CNN Architecture 35116.3.3 Performance Evaluation Measures 35216.4 Conclusion 357Acknowledgments 358Bibliography 35817 Aerial Repair and Aerial Additive Manufacturing 367Yusuf Furkan Kaya, Lachlan Orr, Basaran Bahadir Kocer, and Mirko Kovac17.1 Review of State of the Art in Additive Manufacturing at Architectural Scales 36717.2 Review of Demonstrations of Aerial Manufacturing and Repair 37117.2.1 Demands and Challenges 37417.2.2 Future Prospects 37617.3 Initial Experimental Evaluations 37817.4 Conclusion and Discussion 379Bibliography 379Index 385