Autonomous Vehicles

This edited volume, Autonomous Vehicles, is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of vehicle autonomy. The book comprises nine chapters authored by various researchers and edited by an expert active in the field of study. All chapters are complete in itself but united under a common research study topic. This publication aims to provide a thorough overview of the latest research efforts by international authors, open new possible research paths for further novel developments, and to inspire the younger generations into pursuing relevant academic studies and professional careers within the autonomous vehicle field

Feasibility Study to Determine the Economic and Operational Benefits of Utilizing Unmanned Aerial Vehicles (UAVs)

This project explored the feasibility of using Unmanned Aerial Systems (UASs) in Georgia Department of Transportation (GDOT) operations. The research team conducted 24 interviews with personnel in four GDOT divisions. Interviews focused on (1) the basic goals of the operators in each division, (2) their major decisions for accomplishing those goals, and (3) the information requirements for each decision. Following an interview validation process, a set of UASs design characteristics that fulfill user requirements of each previously identified division was developed. A “House of Quality” viewgraph was chosen to capture the relationships between GDOT tasks and potential UAS aiding those operations. As a result, five reference systems are proposed. The UAS was broken into three components: vehicle, control station, and system. This study introduces a variety of UAS applications in traffic management, transportation and construction disciplines related to DOTs, such as the ability to get real time, digital photographs/videos of traffic scenes, providing a "bird’s eye view" that was previously only available with the assistance of a manned aircraft, integrating aerial data into GDOT drawing software programs, and dealing with restricted or complicated access issues when terrain, area, or the investigated object make it difficult for GDOT personnel to conduct a task. The results of this study could lead to further research on design, development, and field-testing of UAVs for applications identified as beneficial to the Department.Georgia Department of Transportatio

Assessing Wind Impact on Semi-Autonomous Drone Landings for In-Contact Power Line Inspection

In recent years, the use of inspection drones has become increasingly popular for high-voltage electric cable inspections due to their efficiency, cost-effectiveness, and ability to access hard-to-reach areas. However, safely landing drones on power lines, especially under windy conditions, remains a significant challenge. This study introduces a semi-autonomous control scheme for landing on an electrical line with the NADILE drone (an experimental drone based on original LineDrone key features for inspection of power lines) and assesses the operating envelope under various wind conditions. A Monte Carlo method is employed to analyze the success probability of landing given initial drone states. The performance of the system is evaluated for two landing strategies, variously controllers parameters and four level of wind intensities. The results show that a two-stage landing strategies offers higher probabilities of landing success and give insight regarding the best controller parameters and the maximum wind level for which the system is robust. Lastly, an experimental demonstration of the system landing autonomously on a power line is presented

Methodology for precision landing of unmanned aerial vehicles on a mobile base

Mestrado de dupla diplomação com a UTFPR - Universidade Tecnológica Federal do ParanáThe integration of heterogeneous robotic systems is a constant topic today as a promising strategy to overcome the inherent limitations of each system. With this in view, this study explores the development of a precision landing system for Unmanned Aerial Vehicles (UAVs), designed to land autonomously on static and moving targets. To achieve this, a detailed analysis of aspects of the system is first carried out, such as the definition of the fiducial marker, the control architecture, and the definition of gains, followed by the development of the code, which includes the architecture and the interface with an operator. After development, tests begin which are divided into two stages: the first verifies the UAV’s ability to identify and follow moving targets, and the second consists of precision landing experiments in different scenarios. The results of the investigation indicate that the combination of a complete PID controller with Aruco markers is more effective, which is why they were selected for the development of the system. Tracking tests have proven the driver’s ability to guide the UAV to autonomously follow a UGV, although it presents difficulties with high angular speeds. On the other hand, autonomous landing tests showed high efficiency in constant speed scenarios but revealed some failures in situations with sudden changes and requests to the rotation driver.A integração de sistemas robóticos heterogêneos é um tópico constante atualmente como uma estratégia promissora para ultrapassar as limitações inerentes a cada sistema individualmente. Com isso, este estudo explora o desenvolvimento de um sistema de pouso de precisão para Veículos Aéreos Não Tripulados (UAVs), destinado a aterragens em alvos estáticos e em movimento autonomamente. Para isso, primeiro é feita uma análise detalhada de aspectos do sistema, como a definição do marcador fiducial, da arquitetura de controle e definição de ganhos, seguido do desenvolvimento do código, que inclui a arquitetura e a interface com o operador. Após o desenvolvimento, inicia-se os testes que se dividem em duas etapas: a primeira verifica a capacidade do UAV de identificar e seguir alvos em movimento, e a segunda consiste em experimentos de pouso de precisão em diversos cenários. Os resultados da investigação indicam que a combinação de um controlador PID completo com marcadores Aruco é mais eficaz, razão pela qual foram selecionados para o desenvolvimento do sistema. Os testes de rastreamento comprovaram a habilidade do controlador em orientar o UAV para seguir autonomamente um UGV, embora apresente dificuldades com velocidades angulares elevadas. Por outro lado, os testes de pouso autônomo mostraram alta eficiência em cenários de velocidade constante, mas revelaram algumas falhas em situações com mudanças bruscas e desafiadoras para o controlador de rotação

On Aerial Robots with Grasping and Perching Capabilities: A Comprehensive Review

Over the last decade, there has been an increased interest in developing aerial robotic platforms that exhibit grasping and perching capabilities not only within the research community but also in companies across different industry sectors. Aerial robots range from standard multicopter vehicles/drones, to autonomous helicopters, and fixed-wing or hybrid devices. Such devices rely on a range of different solutions for achieving grasping and perching. These solutions can be classified as: 1) simple gripper systems, 2) arm-gripper systems, 3) tethered gripping mechanisms, 4) reconfigurable robot frames, 5) adhesion solutions, and 6) embedment solutions. Grasping and perching are two crucial capabilities that allow aerial robots to interact with the environment and execute a plethora of complex tasks, facilitating new applications that range from autonomous package delivery and search and rescue to autonomous inspection of dangerous or remote environments. In this review paper, we present the state-of-the-art in aerial grasping and perching mechanisms and we provide a comprehensive comparison of their characteristics. Furthermore, we analyze these mechanisms by comparing the advantages and disadvantages of the proposed technologies and we summarize the significant achievements in these two research topics. Finally, we conclude the review by suggesting a series of potential future research directions that we believe that are promising

Unmanned Robotic Systems and Applications

This book presents recent studies of unmanned robotic systems and their applications. With its five chapters, the book brings together important contributions from renowned international researchers. Unmanned autonomous robots are ideal candidates for applications such as rescue missions, especially in areas that are difficult to access. Swarm robotics (multiple robots working together) is another exciting application of the unmanned robotics systems, for example, coordinated search by an interconnected group of moving robots for the purpose of finding a source of hazardous emissions. These robots can behave like individuals working in a group without a centralized control

Proceedings of the International Micro Air Vehicles Conference and Flight Competition 2017 (IMAV 2017)

The IMAV 2017 conference has been held at ISAE-SUPAERO, Toulouse, France from Sept. 18 to Sept. 21, 2017. More than 250 participants coming from 30 different countries worldwide have presented their latest research activities in the field of drones. 38 papers have been presented during the conference including various topics such as Aerodynamics, Aeroacoustics, Propulsion, Autopilots, Sensors, Communication systems, Mission planning techniques, Artificial Intelligence, Human-machine cooperation as applied to drones

Computer Vision Applications for Autonomous Aerial Vehicles

Undoubtedly, unmanned aerial vehicles (UAVs) have experienced a great leap forward over the last decade. It is not surprising anymore to see a UAV being used to accomplish a certain task, which was previously carried out by humans or a former technology. The proliferation of special vision sensors, such as depth cameras, lidar sensors and thermal cameras, and major breakthroughs in computer vision and machine learning fields accelerated the advance of UAV research and technology. However, due to certain unique challenges imposed by UAVs, such as limited payload capacity, unreliable communication link with the ground stations and data safety, UAVs are compelled to perform many tasks on their onboard embedded processing units, which makes it difficult to readily implement the most advanced algorithms on UAVs. This thesis focuses on computer vision and machine learning applications for UAVs equipped with onboard embedded platforms, and presents algorithms that utilize data from multiple modalities. The presented work covers a broad spectrum of algorithms and applications for UAVs, such as indoor UAV perception, 3D understanding with deep learning, UAV localization, and structural inspection with UAVs. Visual guidance and scene understanding without relying on pre-installed tags or markers is the desired approach for fully autonomous navigation of UAVs in conjunction with the global positioning systems (GPS), or especially when GPS information is either unavailable or unreliable. Thus, semantic and geometric understanding of the surroundings become vital to utilize vision as guidance in the autonomous navigation pipelines. In this context, first, robust altitude measurement, safe landing zone detection and doorway detection methods are presented for autonomous UAVs operating indoors. These approaches are implemented on Google Project Tango platform, which is an embedded platform equipped with various sensors including a depth camera. Next, a modified capsule network for 3D object classification is presented with weight optimization so that the network can be fit and run on memory-constrained platforms. Then, a semantic segmentation method for 3D point clouds is developed for a more general visual perception on a UAV equipped with a 3D vision sensor. Next, this thesis presents algorithms for structural health monitoring applications involving UAVs. First, a 3D point cloud-based, drift-free and lightweight localization method is presented for depth camera-equipped UAVs that perform bridge inspection, where GPS signal is unreliable. Next, a thermal leakage detection algorithm is presented for detecting thermal anomalies on building envelopes using aerial thermography from UAVs. Then, building on our thermal anomaly identification expertise gained on the previous task, a novel performance anomaly identification metric (AIM) is presented for more reliable performance evaluation of thermal anomaly identification methods