Bridge Inspection: Human Performance, Unmanned Aerial Systems and Automation

Unmanned aerial systems (UASs) have become of considerable private and commercial interest for a variety of jobs and entertainment in the past 10 years. This paper is a literature review of the state of practice for the United States bridge inspection programs and outlines how automated and unmanned bridge inspections can be made suitable for present and future needs. At its best, current technology limits UAS use to an assistive tool for the inspector to perform a bridge inspection faster, safer, and without traffic closure. The major challenges for UASs are satisfying restrictive Federal Aviation Administration regulations, control issues in a GPS-denied environment, pilot expenses and availability, time and cost allocated to tuning, maintenance, post-processing time, and acceptance of the collected data by bridge owners. Using UASs with self-navigation abilities and improving image-processing algorithms to provide results near real-time could revolutionize the bridge inspection industry by providing accurate, multi-use, autonomous three-dimensional models and damage identification

Applications of Mixed Reality for Smart Aviation Industry: Opportunities and Challenges

Nowadays, mixed reality has improved operational efficiency and enhanced passenger experience in the aviation industry. Integrated with advanced machine learning and artificial intelligence techniques, mixed reality can easily deal with tons of aviation data to support decision-making processes in this industry. The chapter presents the state-of-the-art applications of mixed reality in smart aviation industry. Opportunities and challenges of integrating mixed reality with advanced machine learning and artificial intelligence techniques into the aviation industry are introduced. This chapter focuses on how the integrated mixed reality can improve the quality and reliability of maintenance, operation, piloting, training, and product design in smart aerospace engineering. It also describes autonomous, self-service, and data visualization systems in smart airports to enhance passenger experience. Finally, this chapter discusses airline’s digital-based responses to the COVID-19 crisis

Use of Unmanned Aerial Systems in Civil Applications

Interest in drones has been exponentially growing in the last ten years and these machines are often presented as the optimal solution in a huge number of civil applications (monitoring, agriculture, emergency management etc). However the promises still do not match the data coming from the consumer market, suggesting that the only big field in which the use of small unmanned aerial vehicles is actually profitable is the video-makers’ one. This may be explained partly with the strong limits imposed by existing (and often "obsolete") national regulations, but also - and pheraps mainly - with the lack of real autonomy. The vast majority of vehicles on the market nowadays are infact autonomous only in the sense that they are able to follow a pre-determined list of latitude-longitude-altitude coordinates. The aim of this thesis is to demonstrate that complete autonomy for UAVs can be achieved only with a performing control, reliable and flexible planning platforms and strong perception capabilities; these topics are introduced and discussed by presenting the results of the main research activities performed by the candidate in the last three years which have resulted in 1) the design, integration and control of a test bed for validating and benchmarking visual-based algorithm for space applications; 2) the implementation of a cloud-based platform for multi-agent mission planning; 3) the on-board use of a multi-sensor fusion framework based on an Extended Kalman Filter architecture

Non-Contact Evaluation Methods for Infrastructure Condition Assessment

The United States infrastructure, e.g. roads and bridges, are in a critical condition. Inspection, monitoring, and maintenance of these infrastructure in the traditional manner can be expensive, dangerous, time-consuming, and tied to human judgment (the inspector). Non-contact methods can help overcoming these challenges. In this dissertation two aspects of non-contact methods are explored: inspections using unmanned aerial systems (UASs), and conditions assessment using image processing and machine learning techniques. This presents a set of investigations to determine a guideline for remote autonomous bridge inspections

A Systematic Literature Survey of Unmanned Aerial Vehicle Based Structural Health Monitoring

Unmanned Aerial Vehicles (UAVs) are being employed in a multitude of civil applications owing to their ease of use, low maintenance, affordability, high-mobility, and ability to hover. UAVs are being utilized for real-time monitoring of road traffic, providing wireless coverage, remote sensing, search and rescue operations, delivery of goods, security and surveillance, precision agriculture, and civil infrastructure inspection. They are the next big revolution in technology and civil infrastructure, and it is expected to dominate more than $45 billion market value. The thesis surveys the UAV assisted Structural Health Monitoring or SHM literature over the last decade and categorize UAVs based on their aerodynamics, payload, design of build, and its applications. Further, the thesis presents the payload product line to facilitate the SHM tasks, details the different applications of UAVs exploited in the last decade to support civil structures, and discusses the critical challenges faced in UASHM applications across various domains. Finally, the thesis presents two artificial neural network-based structural damage detection models and conducts a detailed performance evaluation on multiple platforms like edge computing and cloud computing

CONTROL DE BRAZO ROBÓTICO DE TRES GRADOS DE LIBERTAD CON DE PROCESAMIENTO DIGITAL DE IMÁGENES PARA SEGUIMIENTO DE UN BRAZO HUMANO (THREE DEGREE OF FREEDOM ROBOTIC ARM CONTROL WITH DIGITAL IMAGE PROCESSING FOR FOLLOW-UP A HUMAN ARM)

ResumenEn este documento, se describe el desarrollo de un robot planar de tres grados de libertad, para el seguimiento de un brazo real humano mediante Procesamiento Digital de Imágenes PDI, usando una cámara. Mediante un algoritmo que resuelve el modelo cinemático inverso del robot y usando la imagen capturada, se obtienen los ángulos existentes; entre los centros de tres aéreas del brazo humano. Los ángulos son escalados y enviados a una placa arduino. Un control, tipo proporcional, utiliza los errores entre los ángulos del brazo y el robot para mover tres servomotores; los cuales están unidos a los eslabones del robot. Este sistema se realizó con el fin de tener un robot imitador de bajo costo con fines educativos y de experimentación. Como resultado, se obtuvo un brazo robótico que hace seguimiento o imita con sus tres eslabones a los dedos, la palma y el antebrazo del usuario.Palabras Claves: Control, brazo robótico, PDI. AbstractIn this document is described the development of a project that consists of a planar robot of three degrees of freedom for the follow-up of a real human arm by means of Digital Image Processing DIP using a camera.  Using an algorithm that solves the inverse kinematic model of the robot and using the captured image, the angles between the geometric centers of the human arm are obtained. These angles are scaled and sent to an Arduino board. A type of proportional control uses the angle errors between the arm and the robot to move three servo motors which are attached to the links of the robot. This system was made in order to have a low-cost mimic robot for educational and experimentation purposes. A robotic arm that follow-up or mimics with its three links to the user's fingers, palm and forearm was obtained as a result.Keywords: Control, robotic arm, DIP

Reliable and Safe Motion Control of Unmanned Vehicles

Unmanned vehicles (UVs) are playing an increasingly significant role in modern daily life. In the past decades, numerous commercial, scientific, and military communities across the world are developing fully autonomous UVs for a variety of applications, such as environmental monitoring and surveillance, post-disaster search and rescue, border patrol, natural resources exploration, and experimental platforms for new technologies verification. The excessive opportunities and threats that come along with these diverse applications have created a niche demand for UVs to extend their capabilities to perform more sophisticated and hazardous missions with greater autonomy, lower costs of development and operation, improved personnel safety and security, extended operational range (reliability) and precision, as well as increased flexibility in sophisticated environments including so-called dirty, dull, harsh, and dangerous missions. In order to successfully and effectively execute missions and meet their corresponding performance criteria and overcome these ever-increasing challenges, greater autonomy together with more advanced reliable and safe motion control systems are required to offer the critical technologies for ensuring intelligent, safe, reliable, and efficient control of UVs in the presence of disturbances, actuator saturation, and even actuator faults, especially for practical applications. This thesis concentrates on the development of different reliable and safe motion control algorithms/strategies applicable to UVs, in particular, unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs). A number of contributions pertaining to the fault detection and diagnosis (FDD), fault-tolerant control (FTC), disturbance estimation and compensation, and actuator saturation avoidance have been made in this thesis. In addition to the control problems, this thesis also presents several guidance-related contributions, including adaptive observer-based line-of-sight (LOS) guidance law, time-varying lookahead distance scheme, piecewise path switching criterion for guiding a single UV, as well as a proportional-integral (PI) type of leader-follower formation guidance strategy for a group of UVs

Machine learning and mixed reality for smart aviation: applications and challenges

The aviation industry is a dynamic and ever-evolving sector. As technology advances and becomes more sophisticated, the aviation industry must keep up with the changing trends. While some airlines have made investments in machine learning and mixed reality technologies, the vast majority of regional airlines continue to rely on inefficient strategies and lack digital applications. This paper investigates the state-of-the-art applications that integrate machine learning and mixed reality into the aviation industry. Smart aerospace engineering design, manufacturing, testing, and services are being explored to increase operator productivity. Autonomous systems, self-service systems, and data visualization systems are being researched to enhance passenger experience. This paper investigate safety, environmental, technological, cost, security, capacity, and regulatory challenges of smart aviation, as well as potential solutions to ensure future quality, reliability, and efficiency

Multi-Scale detection, mapping, and modelling geomorphic change in gravel-bed rivers with UAV remote sensing

Fluvial science is in particular need of surveying tools which can rapidly and accurately capture topographic data. The use of low-cost, consumer grade UAV (unmanned aerial vehicle) systems and Structure from Motion (SfM) processing methods has seen successful adoption by many other earth surface processes sub-fields however their use for monitoring within the field of fluvial geomorphology remains limited. This study tests the applicability of UAV photogrammetry to fluvial surveying, capturing centimetric resolution data across kilometric scales, providing an ideal perspective for geomorphic process interpretation. For a historically modified UK case study, four series of very high resolution DEMs (digital elevation model) and orthomosaic imagery are produced for a 2km reach of quasi-wandering gravel-bed river. Comparative analyses of DEMs between 2016 and 2018 reveals widening of the incised margin and significant geomorphic evolution characteristic of re-naturalization following the termination of gravel mining, channelization, and resultant aggressive incision. Whole reach volumetric analysis reveals a negative sediment budget approximating a net loss of 250m3/year. Budgetary segregation shows 22% of eroded material is sourced from the banks of the inset wandering margin and is a possible cause of a general fining (30% reduction in mean b axis) of bed material within active channels, detectable by grain scale analysis of high-resolution orthomosaic imagery. Vertical scour is seen to be prevented, even under extreme flows (~100 m3/s-1), by a bed armouring effect which is sustained by liberation of coarse clasts from the floodplain via lateral erosion and bank collapse. Woody debris dynamics, gravel bar creation and migration are intricately modelled throughout the site, their presence seen to be affecting flow-prioritization of sub-channels inside the incised margin. UAV surveying workflows and processing protocols are also developed for fluvial science: A means to neutralize and filter out surface error caused by vegetation occlusion in the SfM workflow, and a method to correct for geo-referencing error in large DEMs. Geomorphic findings at this UK case study hold valuable and transferable insights to river re-naturalization in the context of gravel extraction and channelization