by DR. UDAY KUMAR., Dammika Seneviratne, and Diego Galar
Contents
Authors ………………………………………………………………… ix
1. Introduction ………………………………………………………………………. 1
1.1 Autonomous Vehicles ……………………………………. 1
1.2 Industrial Assets ………………………………………………………. 21
1.3 Inspection of Industrial Assets …………………………………………………. 26
1.4 Maintenance of Industrial Assets …………………………………………… 28
References ………………………………………………………………… 33
2.1 History of Development of Autonomous Robots ………………………………………………………… 37
2.2 Dynamics and Machine Architectures ……………………………………………………………………… 48
2.3 Robots and Machine Intelligence …………………………………………………………………………….. 52
2.4 Programming Autonomous Robots ………………………………………………………………………….. 57
2.5 Adaptive Algorithms and Their Use …………………………………………………………………………. 62
References ……………………………………………. 70
3.1 Autonomous Vehicle Inspection Platform …………………………………………………………………. 73
3.2 Inspection Communications and Transport Security ………………………………………………….. 80
3.3 Obstacle Avoidance ………………………………………………………………………………………………… 83
3.4 Inspection Modes and Content ………………………………………………………………………………… 87
3.5 Inspection Methods ………………………………………………………………………… 93
References ………………………………………………………. 106
4. Sensors for Autonomous Vehicles in Infrastructure Inspection Applications ……………………111
4.1 Sensors and Sensing Strategies…………………………………………………………………………………111
4.2 Sensor Types: Introduction ……………………………………………………………………………………..115
4.3 Sensors for Military Missions………………………………………………………………………………… 130
4.4 Sensor-Based Localization and Mapping ………………………………………………………………….133
4.5 Sensor Fusion, Sensor Platforms, and Global Positioning System…………………………………141
References …………………………………… 150
5.1 Data Acquisition Principle and Process for Laser Scanning, Visual Imaging,
Infrared Imaging, UV Imaging 155
5.2 Cloud Data Post-Processing Technology……………………………………………………………………174
5.3 Cloud Data Intelligent Diagnosis ……………………………………………………………………………..179
References …………………………………………………………………………….183
6.1 Overview ………………………………………………………………………………………………………………187
6.2 Line Security Diagnosis for Multisource Data Fusion ………………………………………………. 206
6.3 Three-Dimensional Visualization Applications …………………………………………………………216
References ……………………………………………………………………. 220
Contents
7.1 Communication Methods………………………………………………………………………………………. 227
7.2 Radio Communication ………………………………………………………………………………………….. 230
7.3 Mid-Air Collision (MAC) Avoidance ……………………………………………………………………… 235
7.4 Communications Data Rate and Bandwidth Usage …………………………………………………… 241
7.5 A ntenna Types …………………………………………………………………………………………………….. 244
7.6 Tracking with Multiple Autonomous Vehicles …………………………………………………………. 265
References ………………………………………………………………………… 268
8.1 Power Line Inspection ………………………………………………………………………………………….. 271
8.2 B uilding Monitoring …………………………………………………………………………………………….. 280
8.3 Railway Infrastructure Inspection ………………………………………………………………………….. 288
8.4 Waterways and Other Infrastructures ……………………………………………………………………… 294
References …………………………………………………………………… 303
9.1 Repeated Inspections and Failure Identification ………………………………………………………. 307
9.2 Autonomous Vehicle Emergency Inspection Applications ………………………………………….313
9.3 Autonomous Vehicle Navigation Security………………………………………………………………… 322
References ……………………………………………………………………………. 337
10.1 Artificial Intelligence Techniques Used in AVs …………………………………………………………341
10.2 Artificial Intelligence Approaches for Inspection and Maintenance …………………………… 346
10.3 Current Developments of AVs with AI ……………………………………………………………………..353
References ……………………………………………………………………………..361
11.1 Big Data Analytics and Cyber-Physical Systems ……………………………………………………… 365
11.2 Big Data Analytics in Inspection and Maintenance ………………………………………………….. 376
11.3 Integration of Big Data Analytics in AV Inspection and Maintenance ………………………….381
11.4 Utilization of AVs in Industry 4.0 Environment ……………………………………………………….. 384
References …………………………………………………………….. 388
Index …………………………………………………………………………… 393
Preface
Autonomous vehicle (AV) technology offers the possibility of fundamentally changing our lives, perhaps most visibly in the transportation sector. Equipping cars and light vehicles with this technology will likely reduce crashes, energy consumption, the costs of congestion, and pollution. In a wider sense, AV technology has the potential to substantially affect safety, energy use, and, ultimately, land use and the environment. This book begins by explaining what autonomous robots are and noting their potential use in many different applications, not just on the road driving people from place to place but in the work-place for inspections, maintenance, and many other tasks.
The main difficulty is training robots to effectively carry out tasks in different and little-known envi-ronments. Autonomous robots, i.e., freely moving robots that operate without direct human supervision, are expected to function in complex, unstructured environments and make their own decisions on what action to take in any given situation. In such cases, systems based only on classical control theory are insufficient. This requires major improvements in the control architectures. Other architectural needs include the ease and quality of a robot’s specification and programming. Chapter 2 tackles this issue by looking at the programing of autonomous robots and other related details.
Autonomous robots gain information on their surroundings via sensors. The information is processed in the robot’s “brain,” consisting of one or more microcontrollers; after processing, motor signals are sent to the actuators (motors) of the robot and it can take action. Thus, the “brain” is the system that provides an autonomous robot, however simple, with the ability to process information and decide which actions to take.
The emphasis in the development of autonomous robots is currently on speed, energy efficiency, sen-sors for guidance, guidance accuracy, and enabling technologies, such as wireless communication and the global positioning system (GPS). Chapter 7 goes into more detail on the communication aspect, discussing communication methods in general before turning to radio communication specifically. It defines communication as a process of transmitting and receiving meaningful information or intelli-gence. Electronic communication involves converting speech or intelligence into electrical signals using transducers. The signals are processed and transmitted to a receiver. The receiver processes the received signals and drives the transducer which converts the processed signals into speech or intelligence. Put otherwise, transducers convert energy from mechanical to electrical and vice versa. The chapter also defines and explains communications data rate (CDR) and bandwidth usage.
Chapters 2–4 and Chapter 8 give an overview of the development of AVs and distant inspection opera-tions for industrial assets using AVs and unmanned aerial vehicles (UAVs). The chapters discuss the use of AVs in infrastructure inspection and explain the types of sensors used for these applications. Autonomous robots, including UAVs, pipe inspection gauges, and remotely operated vehicles, are cur-rently used in various industrial settings for inspection and maintenance. As autonomous robots can be programmed for repetitive and specific tasks, they can fruitfully be used for the inspection and mainte-nance of industrial assets.
Chapter 5 discusses laser scanning technology, from data acquisition from sensors and intelligent diagnosis to data processing and visualization. It provides a general overview of laser scanning tech-nologies and mentions some specific applications. The chapter also discusses artificial intelligence (AI), defining it as the science and engineering of making intelligent machines, especially intelligent com-puter programs. AI is useful for such activities as searching, recognizing patterns, and making logical inferences. As the chapter points out, AI techniques have potential for system diagnostics.
The inspection of critical structural components, machinery, and spots that are hard to reach is tech-nically complex and mostly done by specially trained staff and/or specialized equipment. Remotely controlled UAVs equipped with high definition photo and video cameras can simplify these inspection tasks. Chapter 6 presents an inspection method and three-dimensional visualizations that lead to critical failure detection by AVs and UAVs (developed in Chapter 9). It also analyzes autonomous inspection and maintenance with AI infiltration (developed in Chapter 10) and Big Data analytics for AV inspec-tion and maintenance. Essentially, the use of Big Data analytics in maintenance represents the fourth level of maturity in predictive maintenance. The fourth level, Predictive Maintenance 4.0, or PM 4.0, is described at length in Chapter 11.
The final chapter, Chapter 11, analyzes maintenance under a Big Data platform and shows how AI can be applied to classify the likely failure patterns and estimate equipment condition. It explains the impor-tant position of AVs in an Industry 4.0 environment and anticipates their further development. Industry 4.0 includes the complete manufacturing value chain—from raw materials, to unfinished goods, to the production shop floor, to the warehouse, storage, and delivery. Automation is at its core, and robots are an essential part. Inevitably, as smarter environments give rise to more information, robots will become more intelligent and easier to operate. Indeed, the ultimate goal of Industry 4.0 is an autonomous smart factory that can produce customizable products.