1st Edition

Robots, Drones, UAVs and UGVs for Operation and Maintenance

    408 Pages 212 B/W Illustrations
    by CRC Press

    Industrial assets (such as railway lines, roads, pipelines) are usually huge, span long distances, and can be divided into clusters or segments that provide different levels of functionality subject to different loads, degradations and environmental conditions, and their efficient management is necessary. The aim of the book is to give comprehensive understanding about the use of autonomous vehicles (context of robotics) for the utilization of inspection and maintenance activities in industrial asset management in different accessibility and hazard levels. The usability of deploying inspection vehicles in an autonomous manner is explained with the emphasis on integrating the total process.

    Key Features

    • Aims for solutions for maintenance and inspection problems provided by robotics, drones, unmanned air vehicles and unmanned ground vehicles
    • Discusses integration of autonomous vehicles for inspection and maintenance of industrial assets
    • Covers the industrial approach to inspection needs and presents what is needed from the infrastructure end
    • Presents the requirements for robot designers to design an autonomous inspection and maintenance system
    • Includes practical case studies from industries

    Chapter 1 Introduction

    1.1 Autonomous Vehicles

    1.2 Industrial Assets

    1.3 Inspection of Industrial Assets

    1.4 Maintenance of Industrial Assets


    Chapter 2 Development of Autonomous Vehicles

    2.1 History of development of Autonomous robots

    2.2 Dynamics and Machine Architectures

    2.3 Robots and Machine Intelligence

    2.4 Programming of Autonomous Robots

    2.5 Adaptive Algorithms and Utilization

    Chapter 3 Distant Inspection Operations for industrial Assets

    3.1 Autonomous Vehicle Inspection Platform

    3.2 Inspection Communications and Transport Security

    3.3 Obstacle Avoidance

    3.4 Inspection Modes and Content

    3.5 Inspection Methods


    Chapter 4 Sensors for Autonomous Vehicles in Infrastructure Inspection Applications

    4.1 Sensors and sensing strategies

    4.2 Sensor types: introduction

    4.3 Sensors for military missions

    4.4 Sensor-based localization and mapping

    4.5 Sensor fusion, sensor platforms and Global Positioning System


    Chapter 5 Data acquisition and intelligent diagnosis

    3.1 Data acquisition principle and process for laser scanning, visual imaging, infrared imaging, UV image

    5.2 Cloud data post-processing technology

    5.3 Cloud data intelligent diagnosis


    Chapter 6 Inspection expert diagnosis and three-dimensional visualization

    6.1 Overview

    6.2 Line security diagnosis for multi-source data fusion

    6.3 Three-dimensonal visualization applications


    Chapter 7 Communications

    7.1 Communication Methods

    7.2 Radio Communication

    7.3 Mid-Air Collision (MAC) Avoidance

    7.4 Communications Data Rate and Bandwidth Usage

    7.5 Antenna Types

    7.6 Tracking with Multiple Autonomous Vehicles


    Chapter 8 Autonomous vehicles for infrastructure inspection applications

    8.1 Power Line Inspection

    8.2 Building Monitoring

    8.3 Railway Infrastructure Inspection

    8.4 Waterways and Other Infrastructures


    Chapter 9 Critical Failure Detection Application In Autonomous Vehicles

    9.1 Repeated Inspections and Failure Identification

    9.2 Autonomous Vehicle Emergency Inspection Applications

    9.3 Autonomous Vehicle Navigation Security


    Chapter 10 Autonomous inspection and maintenance with artificial intelligent infiltration

    10.1 Artificial Intelligent Techniques Used in AVs

    10.2 Artificial Intelligent Approaches for Inspection and Maintenance

    10.3 Current developments of AVs with AI


    Chapter 11 Big Data and Analytics for AV Inspection and maintenance

    11.1 Big Data Analytics and Cyber-Physical Systems

    11.2 Big Data Analytics in Inspection and Maintenance

    11.3 Integration of Big Data Analytics in AV Inspection and Maintenance

    11.4 Utilization of AVs in Industry 4.0 Environment



    Diego Galar, Uday Kumar, Dammika Seneviratne