Introduction to UAV Systems

This chapter provides the background and context for unmanned aerial vehicles (UAVs) and UAV networks with a focus on their civilian applications. It discusses, for example, the types of UAVs, fuel, payload capacity, speed, and endurance. It will also discuss the state-of-the-art in engineering and technology aspects of UAVs and UAV networks and the advantages of UAV networks, including enhanced situational awareness and reduced latency in communications among the UAVs. It presents the applications of UAV networks, research opportunities, and challenges involved in designing, developing, and deploying UAV networks, and the roadmap for research in UAV networks

Advanced air mobility operation and infrastructure for sustainable connected eVTOL vehicle

Advanced air mobility (AAM) is an emerging sector in aviation aiming to offer secure, efficient, and eco-friendly transportation utilizing electric vertical takeoff and landing (eVTOL) aircraft. These vehicles are designed for short-haul flights, transporting passengers and cargo between urban centers, suburbs, and remote areas. As the number of flights is expected to rise significantly in congested metropolitan areas, there is a need for a digital ecosystem to support the AAM platform. This ecosystem requires seamless integration of air traffic management systems, ground control systems, and communication networks, enabling effective communication between AAM vehicles and ground systems to ensure safe and efficient operations. Consequently, the aviation industry is seeking to develop a new aerospace framework that promotes shared aerospace practices, ensuring the safety, sustainability, and efficiency of air traffic operations. However, the lack of adequate wireless coverage in congested cities and disconnected rural communities poses challenges for large-scale AAM deployments. In the immediate recovery phase, incorporating AAM with new air-to-ground connectivity presents difficulties such as overwhelming the terrestrial network with data requests, maintaining link reliability, and managing handover occurrences. Furthermore, managing eVTOL traffic in urban areas with congested airspace necessitates high levels of connectivity to support air routing information for eVTOL vehicles. This paper introduces a novel concept addressing future flight challenges and proposes a framework for integrating operations, infrastructure, connectivity, and ecosystems in future air mobility. Specifically, it includes a performance analysis to illustrate the impact of extensive AAM vehicle mobility on ground base station network infrastructure in urban environments. This work aims to pave the way for future air mobility by introducing a new vision for backbone infrastructure that supports safe and sustainable aviation through advanced communication technology

Research Experiences for Teachers in Sensor Networks

This report discusses research on cooperation of autonomous NXT robots using Bluetooth wireless technology. The research project consisted of using Bluetooth technology to coordinate movements between two agents. This research is part of Research Experiences for Teachers (RET) in Sensor Education, a National Science Foundation (NSF) funded grant project

A Traffic Control Framework for Uncrewed Aircraft Systems

The exponential growth of Advanced Air Mobility (AAM) services demands assurances of safety in the airspace. This research a Traffic Control Framework (TCF) for developing digital flight rules for Uncrewed Aircraft System (UAS) flying in designated air corridors. The proposed TCF helps model, deploy, and test UAS control, agents, regardless of their hardware configurations. This paper investigates the importance of digital flight rules in preventing collisions in the context of AAM. TCF is introduced as a platform for developing strategies for managing traffic towards enhanced autonomy in the airspace. It allows for assessment and evaluation of autonomous navigation, route planning, obstacle avoidance, and adaptive decision making for UAS. It also allows for the introduction and evaluation of advance technologies Artificial Intelligence (AI) and Machine Learning (ML) in a simulation environment before deploying them in the real world. TCF can be used as a tool for comprehensive UAS traffic analysis, including KPI measurements. It offers flexibility for further testing and deployment laying the foundation for improved airspace safety - a vital aspect of UAS technological advancement. Finally, this papers demonstrates the capabilities of the proposed TCF in managing UAS traffic at intersections and its impact on overall traffic flow in air corridors, noting the bottlenecks and the inverse relationship safety and traffic volume.Comment: 6 pages, 7 figure

Research Experiences for Teachers in Sensor Networks

This report discusses research on applications of logic flowcharting with a focus in autonomous robotic operations. This research project is part of Research Experiences for Teachers (RET) in Sensor Networks, a National Science Foundation (NSF) funded grant project