QoS-Aware 3D Coverage Deployment of UAVs for Internet of Vehicles in Intelligent Transportation

It is a challenging problem to characterize the air-to-ground (A2G) channel and identify the best deployment location for 3D UAVs with the QoS awareness. To address this problem, we propose a QoS-aware UAV 3D coverage deployment algorithm, which simulates the three-dimensional urban road scenario, considers the UAV communication resource capacity and vehicle communication QoS requirements comprehensively, and then obtains the optimal UAV deployment position by improving the genetic algorithm. Specifically, the K-means clustering algorithm is used to cluster the vehicles, and the center locations of these clusters serve as the initial UAV positions to generate the initial population. Subsequently, we employ the K-means initialized grey wolf optimization (KIGWO) algorithm to achieve the UAV location with an optimal fitness value by performing an optimal search within the grey wolf population. To enhance the algorithm's diversity and global search capability, we randomly substitute this optimal location with one of the individual locations from the initial population. The fitness value is determined by the total number of vehicles covered by UAVs in the system, while the allocation scheme's feasibility is evaluated based on the corresponding QoS requirements. Competitive selection operations are conducted to retain individuals with higher fitness values, while crossover and mutation operations are employed to maintain the diversity of solutions. Finally, the individual with the highest fitness, which represents the UAV deployment position that covers the maximum number of vehicles in the entire system, is selected as the optimal solution. Extensive experimental results demonstrate that the proposed algorithm can effectively enhance the reliability and vehicle communication QoS

A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles

In recent years, there has been a dramatic increase in the use of unmanned aerial vehicles (UAVs), particularly for small UAVs, due to their affordable prices, ease of availability, and ease of operability. Existing and future applications of UAVs include remote surveillance and monitoring, relief operations, package delivery, and communication backhaul infrastructure. Additionally, UAVs are envisioned as an important component of 5G wireless technology and beyond. The unique application scenarios for UAVs necessitate accurate air-to-ground (AG) propagation channel models for designing and evaluating UAV communication links for control/non-payload as well as payload data transmissions. These AG propagation models have not been investigated in detail when compared to terrestrial propagation models. In this paper, a comprehensive survey is provided on available AG channel measurement campaigns, large and small scale fading channel models, their limitations, and future research directions for UAV communication scenarios

Self-Evolving Integrated Vertical Heterogeneous Networks

6G and beyond networks tend towards fully intelligent and adaptive design in order to provide better operational agility in maintaining universal wireless access and supporting a wide range of services and use cases while dealing with network complexity efficiently. Such enhanced network agility will require developing a self-evolving capability in designing both the network architecture and resource management to intelligently utilize resources, reduce operational costs, and achieve the coveted quality of service (QoS). To enable this capability, the necessity of considering an integrated vertical heterogeneous network (VHetNet) architecture appears to be inevitable due to its high inherent agility. Moreover, employing an intelligent framework is another crucial requirement for self-evolving networks to deal with real-time network optimization problems. Hence, in this work, to provide a better insight on network architecture design in support of self-evolving networks, we highlight the merits of integrated VHetNet architecture while proposing an intelligent framework for self-evolving integrated vertical heterogeneous networks (SEI-VHetNets). The impact of the challenges associated with SEI-VHetNet architecture, on network management is also studied considering a generalized network model. Furthermore, the current literature on network management of integrated VHetNets along with the recent advancements in artificial intelligence (AI)/machine learning (ML) solutions are discussed. Accordingly, the core challenges of integrating AI/ML in SEI-VHetNets are identified. Finally, the potential future research directions for advancing the autonomous and self-evolving capabilities of SEI-VHetNets are discussed.Comment: 25 pages, 5 figures, 2 table

Optimizing the Placement of Multiple UAV--LiDAR Units Under Road Priority and Resolution Requirements

Real-time road traffic information is crucial for intelligent transportation systems (ITS) applications, like traffic navigation or emergency response management, but acquiring such data is tremendously challenging in practice because of the high costs and inefficient placement of sensors. Some modern ITS applications contribute to this problem by equipping vehicles with multiple light detection and ranging (LiDAR) sensors, which are expensive and gather data inefficiently; one solution that avoids vehicle-mounted LiDAR acquisition has been to install elevated LiDAR instruments along roadways, but this approach remains unrefined. The eventual development of sixth-generation (6G) wireless communication will enable new, creative solutions to solve these challenges. One new solution is to deploy multiple multirotor unmanned aerial vehicles (UAVs) outfitted with LiDAR sensors (ULiDs) to acquire data remotely. These ULiDs can capture accurate and real-time road traffic information for ITS applications while maximizing the capabilities of LiDAR sensors, which in turn reduces the number of sensors required. Accordingly, this thesis aims to find the optimal 3D placement of multiple ULiDs to maximize road coverage efficiency for ITS purposes. The formulated optimization problem is constrained by unique ULiD specifications, including field-of-view (FoV), point cloud resolution, geographic information system location, and road segment coverage priorities. A computational intelligent algorithm based on particle swarm optimization is proposed to solve the designed optimization problem. Furthermore, this thesis illustrates the benefits of using the proposed algorithm over existing baselines --Abstract, p. ii

Collaborative autonomy in heterogeneous multi-robot systems

As autonomous mobile robots become increasingly connected and widely deployed in different domains, managing multiple robots and their interaction is key to the future of ubiquitous autonomous systems. Indeed, robots are not individual entities anymore. Instead, many robots today are deployed as part of larger fleets or in teams. The benefits of multirobot collaboration, specially in heterogeneous groups, are multiple. Significantly higher degrees of situational awareness and understanding of their environment can be achieved when robots with different operational capabilities are deployed together. Examples of this include the Perseverance rover and the Ingenuity helicopter that NASA has deployed in Mars, or the highly heterogeneous robot teams that explored caves and other complex environments during the last DARPA Sub-T competition. This thesis delves into the wide topic of collaborative autonomy in multi-robot systems, encompassing some of the key elements required for achieving robust collaboration: solving collaborative decision-making problems; securing their operation, management and interaction; providing means for autonomous coordination in space and accurate global or relative state estimation; and achieving collaborative situational awareness through distributed perception and cooperative planning. The thesis covers novel formation control algorithms, and new ways to achieve accurate absolute or relative localization within multi-robot systems. It also explores the potential of distributed ledger technologies as an underlying framework to achieve collaborative decision-making in distributed robotic systems. Throughout the thesis, I introduce novel approaches to utilizing cryptographic elements and blockchain technology for securing the operation of autonomous robots, showing that sensor data and mission instructions can be validated in an end-to-end manner. I then shift the focus to localization and coordination, studying ultra-wideband (UWB) radios and their potential. I show how UWB-based ranging and localization can enable aerial robots to operate in GNSS-denied environments, with a study of the constraints and limitations. I also study the potential of UWB-based relative localization between aerial and ground robots for more accurate positioning in areas where GNSS signals degrade. In terms of coordination, I introduce two new algorithms for formation control that require zero to minimal communication, if enough degree of awareness of neighbor robots is available. These algorithms are validated in simulation and real-world experiments. The thesis concludes with the integration of a new approach to cooperative path planning algorithms and UWB-based relative localization for dense scene reconstruction using lidar and vision sensors in ground and aerial robots

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

Optimization and Communication in UAV Networks

UAVs are becoming a reality and attract increasing attention. They can be remotely controlled or completely autonomous and be used alone or as a fleet and in a large set of applications. They are constrained by hardware since they cannot be too heavy and rely on batteries. Their use still raises a large set of exciting new challenges in terms of trajectory optimization and positioning when they are used alone or in cooperation, and communication when they evolve in swarm, to name but a few examples. This book presents some new original contributions regarding UAV or UAV swarm optimization and communication aspects

A Comprehensive Review of AI-enabled Unmanned Aerial Vehicle: Trends, Vision , and Challenges

In recent years, the combination of artificial intelligence (AI) and unmanned aerial vehicles (UAVs) has brought about advancements in various areas. This comprehensive analysis explores the changing landscape of AI-powered UAVs and friendly computing in their applications. It covers emerging trends, futuristic visions, and the inherent challenges that come with this relationship. The study examines how AI plays a role in enabling navigation, detecting and tracking objects, monitoring wildlife, enhancing precision agriculture, facilitating rescue operations, conducting surveillance activities, and establishing communication among UAVs using environmentally conscious computing techniques. By delving into the interaction between AI and UAVs, this analysis highlights the potential for these technologies to revolutionise industries such as agriculture, surveillance practices, disaster management strategies, and more. While envisioning possibilities, it also takes a look at ethical considerations, safety concerns, regulatory frameworks to be established, and the responsible deployment of AI-enhanced UAV systems. By consolidating insights from research endeavours in this field, this review provides an understanding of the evolving landscape of AI-powered UAVs while setting the stage for further exploration in this transformative domain