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[null,"1.","Record Nr.",null,"UNINA9911018914703321"]
[null,null,"Autore",null,"Liu Dikai"]
[null,null,"Titolo",null,"Infrastructure Robotics : Methodologies, Robotic Systems and Applications"]
[null,null,"Pubbl/distr/stampa",null,"Newark : , : John Wiley & Sons, Incorporated, , 2024"]
[{"$nulls":4},"©2024"]
[null,null,"ISBN",null,"9781394162857"]
[{"$nulls":4},"1394162855"]
[{"$nulls":4},"9781394162871"]
[{"$nulls":4},"1394162871"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (435 pages)"]
[null,null,"Collana",null,"IEEE Press Series on Systems Science and Engineering Series"]
[null,null,"Disciplina",null,"629.892"]
[null,null,"Soggetti",null,"Robotics"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Cover -- Title Page -- Copyright -- Contents -- About the Editors -- Preface -- Acronyms -- Part I Methodologies -- Chapter 1 Infrastructure Robotics: An Introduction -- 1.1 Infrastructure Inspection and Maintenance -- 1.2 Infrastructure Robotics -- 1.2.1 Inspection and Maintenance of Steel Bridges -- 1.2.2 Climbing and Wheeled Robots for Inspection of Truss Structures -- 1.2.3 Robots for Underwater Infrastructure Maintenance -- 1.3 Considerations in Infrastructure Robotics Research -- 1.4 Opportunities and Challenges -- 1.5 Concluding Remarks -- Bibliography -- Chapter 2 Design of Infrastructure Robotic Systems -- 2.1 Special Features of Infrastructure -- 2.2 The Design Process -- 2.3 Types of Robots and Their Design and Operation -- 2.4 Software System Design -- 2.5 An Example: Development of the CROC Design Concept -- 2.6 Some Other Examples -- 2.7 Actuator Systems -- 2.8 Concluding Remarks -- Bibliography -- Chapter 3 Perception in Complex and Unstructured Infrastructure Environments -- 3.1 Introduction -- 3.2 Sensor Description -- 3.2.1 2D LiDAR -- 3.2.2 3D LiDAR -- 3.2.3 Sonar -- 3.2.4 Monocular Camera -- 3.2.5 Stereo Camera -- 3.2.6 GRB‐D Camera -- 3.3 Problem Description -- 3.4 Theoretical Foundations -- 3.4.1 Extended Kalman Filter -- 3.4.2 Nonlinear Least Squares -- 3.4.3 Environment Representations -- 3.4.4 Mapping Techniques -- 3.4.5 Localization Techniques -- 3.4.6 SLAM Techniques -- 3.5 Implementation -- 3.5.1 "]
[{"$nulls":4},"Localization -- 3.5.2 SLAM -- 3.6 Case Studies -- 3.6.1 Mapping in Confined Space -- 3.6.2 Localization in Confined Space -- 3.6.3 SLAM in Underwater Bridge Environment -- 3.7 Conclusion and Discussion -- Bibliography -- Chapter 4 Machine Learning and Computer Vision Applications in Civil Infrastructure Inspection and Monitoring -- 4.1 Introduction -- 4.2 GNN‐Based Pipe Failure Prediction -- 4.2.1 Background."]
[{"$nulls":4},"4.2.2 Problem Formulation -- 4.2.3 Data Preprocessing -- 4.2.4 GNN Learning -- 4.2.5 Failure Pattern Learning -- 4.2.6 Failure Predictor -- 4.2.7 Experimental Study -- 4.3 Computer Vision‐Based Signal Aspect Transition Detection -- 4.3.1 Background -- 4.3.2 Signal Detection Model -- 4.3.3 Track Detection Model -- 4.3.4 Optimization for Target Locating -- 4.4 Conclusion and Discussion -- Bibliography -- Chapter 5 Coverage Planning and Motion Planning of Intelligent Robots for Civil Infrastructure Maintenance -- 5.1 Introduction to Coverage and Motion Planning -- 5.2 Coverage Planning Algorithms for a Single Robot -- 5.2.1 An Offline Coverage Planning Algorithm -- 5.2.2 A Real‐Time Coverage Planning Algorithm -- 5.3 Coverage Planning Algorithms for Multiple Robots -- 5.3.1 Base Placement Optimization -- 5.3.2 Area Partitioning and Allocation -- 5.3.3 Adaptive Coverage Path Planning -- 5.4 Conclusion -- Bibliography -- Chapter 6 Methodologies in Physical Human-Robot Collaboration for Infrastructure Maintenance -- 6.1 Introduction -- 6.2 Autonomy, Tele‐Operation, and pHRC -- 6.2.1 Autonomous Robots -- 6.2.2 Teleoperated Robots -- 6.2.3 Physical Human-Robot Collaboration -- 6.3 Control Methods -- 6.3.1 Motion Control -- 6.3.2 Force Control -- 6.4 Adaptive Assistance Paradigms -- 6.4.1 Manually Adapted Assistance -- 6.4.2 Assistance‐As‐Needed Paradigms -- 6.4.3 Performance‐Based Assistance -- 6.4.4 Physiology‐Based Assistance -- 6.5 Safety Framework for pHRC -- 6.6 Performance‐Based Role Change -- 6.7 Case Study -- 6.8 Discussion -- Acknowledgements -- Bibliography -- Part II Robotic System Design and Applications -- Chapter 7 Steel Bridge Climbing Robot Design and Development -- 7.1 Introduction -- 7.2 Recent Climbing Robot Platforms Developed by the ARA Lab -- 7.3 Overall Design -- 7.3.1 Mechanical Design and Analysis -- 7.4 Overall Control Architecture."]
[{"$nulls":4},"7.4.1 Control System Framework -- 7.5 Experiment Results -- 7.5.1 Switching Control -- 7.5.2 Robot Navigation in Mobile and Worming Transformation -- 7.5.3 Robot Deployment -- 7.6 Conclusion and Future Work -- Bibliography -- Chapter 8 Underwater Robots for Cleaning and Inspection of Underwater Structures -- 8.1 Introduction to Maintenance of Underwater Structures -- 8.2 Robot System Design -- 8.2.1 Hull Design and Maneuvering System -- 8.2.2 Robot Arms for Docking and Water‐Jet Cleaning -- 8.3 Sensing and Perception in Underwater Environments -- 8.3.1 Underwater Simultaneous Localization and Mapping (SLAM) Around Bridge Piles -- 8.3.2 Marine Growth Identification -- 8.4 Software Architecture -- 8.5 Robot Navigation, Motion Planning and System Integration -- 8.5.1 Localization and Navigation in Open Water -- 8.5.2 System Integration -- 8.6 Testing in a Lab Setup and Trials in the Field -- 8.6.1 Operation Procedure -- 8.6.2 Autonomous Navigation in Narrow Environments -- 8.6.3 Vision‐Based Marine Growth Removing Process -- 8.6.4 Inspection and Marine Growth Identification -- 8.7 Reflection and Lessons Learned -- 8.8 Conclusion and Future Work -- Acknowledgments -- Bibliography -- Chapter 9 Tunnel Structural Inspection and Assessment Using an Autonomous Robotic System -- 9.1 Introduction -- 9.2 ROBO‐SPECT Project -- 9.2.1 Robotic System -- 9.2.2 Intelligent Global Controller -- 9.2.3 Ground Control Station -- 9.2.4 Structural Assessment Tool -- 9.3 Inspection Procedure -- 9.4 "]
[{"$nulls":4},"Extended Kalman Filter for Mobile Vehicle Localization -- 9.5 Mobile Vehicle Navigation -- 9.6 Field Experimental Results -- 9.7 Conclusion -- Bibliography -- Chapter 10 BADGER: Intelligent Robotic System for Underground Construction -- 10.1 Introduction -- 10.2 Boring Systems and Methods -- 10.2.1 Directional Drilling Methods -- 10.2.2 Drilling Robotic Systems."]
[{"$nulls":4},"10.3 Main Drawbacks -- 10.4 BADGER System and Components -- 10.4.1 Main Systems Description -- 10.4.2 BADGER Operation -- 10.5 Future Trends -- Bibliography -- Chapter 11 Robots for Underground Pipe Condition Assessment -- 11.1 Introduction to Ferro‐Magnetic Pipeline Maintenance -- 11.1.1 NDT Inspection Taxonomy -- 11.2 Inspection Robots -- 11.2.1 Robot Kinematics and Locomotion -- 11.3 PEC Sensing for Ferromagnetic Wall Thickness Mapping -- 11.3.1 Hardware and Software System Architecture -- 11.4 Gaussian Processes for Spatial Regression from Sampled Inspection Data -- 11.4.1 Gaussian Processes -- 11.5 Field Robotic CA Inspection Results -- 11.6 Concluding Remarks -- Bibliography -- Chapter 12 Robotics and Sensing for Condition Assessment of Wastewater Pipes -- 12.1 Introduction -- 12.2 Nondestructive Sensing System for Condition Assessment of Sewer Walls -- 12.3 Robotic Tool for Field Deployment -- 12.4 Laboratory Evaluation -- 12.5 Field Deployment and Evaluation -- 12.6 Lessons Learned and Future Directions -- 12.7 Concluding Remarks -- Bibliography -- Chapter 13 A Climbing Robot for Maintenance Operations in Confined Spaces -- 13.1 Introduction -- 13.2 Robot Design -- 13.3 Methodologies -- 13.3.1 Perception -- 13.3.2 Control -- 13.3.3 Planning of Robot Body Motion -- 13.4 Experiments and Results -- 13.4.1 Experiment Setup -- 13.4.2 Lab Test Results -- 13.4.3 Field Trials in a Steel Bridge -- 13.5 Discussion -- 13.6 Conclusion -- Bibliography -- Chapter 14 Multi‐UAV Systems for Inspection of Industrial and Public Infrastructures -- 14.1 Introduction -- 14.2 Multi‐UAV Inspection of Electrical Power Systems -- 14.2.1 Use Cases -- 14.2.2 Architecture -- 14.3 Inspection Planning -- 14.3.1 Vehicle Routing Problem -- 14.4 Onboard Online Semantic Mapping -- 14.4.1 GNSS‐Endowed Mapping System."]
[{"$nulls":4},"14.4.2 Reflectivity and Geometry‐Based Semantic Classification -- 14.4.3 Validation -- 14.5 Conclusion -- Bibliography -- Chapter 15 Robotic Platforms for Inspection of Oil Refineries -- 15.1 Refining Oil for Fuels and Petrochemical Basics -- 15.2 The Inspection Process -- 15.3 Inspection and Mechanical Integrity of Oil Refinery Components -- 15.3.1 Liquid Storage Tank Inspection -- 15.3.2 Pressurized Vessels Inspection -- 15.3.3 Process Pipping -- 15.3.4 Heat Exchanger Bundles -- 15.4 Plant Operations, Surveillance, Maintenance Activities, and Others -- 15.4.1 Surveillance, Operations, and Maintenance of Oil and Gas Refineries -- 15.4.2 Safety and Security -- 15.4.3 Utilities and Support Activities -- 15.5 Robotic Systems for Inspection -- 15.5.1 Robotics for Storage Tanks -- 15.5.2 Robotics for Pressure Vessels -- 15.5.3 Robotics for Process Piping -- 15.5.4 Robotics Heat Exchanger Bundles -- 15.6 Robotics for Plant Operations, Surveillance, Maintenance, and Other Related Activities -- 15.6.1 Operations, Surveillance, and Maintenance of Oil and Gas Refineries with Robotic Systems -- 15.6.2 Safety and Security Robotics -- 15.6.3 Robotics for Utilities and Support Activities -- 15.7 Conclusion -- Chapter 16 Drone‐Based Solar Cell Inspection With Autonomous Deep Learning -- 16.1 Introduction -- 16.1.1 Motivation -- 16.1.2 Related Works -- 16.1.3 Scope -- 16.2 Aerial Robot and Detection Framework -- 16.2.1 Simulation Environment -- 16.2.2 Solar Panel Detection -- 16.2.3 Aerial Robot Trajectory -- 16.2.4 Sensory Instrumentation for Aerial Robot -- 16.3 Learning Framework -- 16.3.1 Dataset Preparation -- "]
[{"$nulls":4},"16.3.2 CNN Architecture -- 16.3.3 Performance Evaluation Measures -- 16.4 Conclusion -- Acknowledgments -- Bibliography -- Chapter 17 Aerial Repair and Aerial Additive Manufacturing."]
[{"$nulls":4},"17.1 Review of State of the Art in Additive Manufacturing at Architectural Scales."]
[null,null,null,"Sommario/riassunto","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."]