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

Design and Test of a UAV Swarm Architecture over a Mesh Ad-Hoc Network

The purpose of this research was to develop a testable swarm architecture such that the swarm of UAVs collaborate as a team rather than acting as several independent vehicles. Commercial-off-the-shelf (COTS) components were used as they were low-cost, readily available, and previously proven to work with at least two networked UAVs. Initial testing was performed via software-in-the-loop (SITL) demonstrating swarming of three simulated multirotor aircraft, then transitioned to real hardware. The architecture was then tested in an outdoor nylon netting enclosure. Command and control (C2) was provided by software implementing an enhanced version of Reynolds’ flocking rules via an onboard companion computer, and UDP multicast messages over a W-Fi mesh ad-hoc network. Experimental results indicate a standard deviation between vehicles of two meters or less, at airspeeds up to two meters per second. This aligns with navigation instrumentation error, permitting safe operation of multiple vehicles within five meters of each other. Qualitative observations indicate this architecture is robust enough to handle more aircraft, pass additional sensor data, and incorporate different swarming algorithms and missions

A Consolidated Review of Path Planning and Optimization Techniques: Technical Perspectives and Future Directions

In this paper, a review on the three most important communication techniques (ground, aerial, and underwater vehicles) has been presented that throws light on trajectory planning, its optimization, and various issues in a summarized way. This kind of extensive research is not often seen in the literature, so an effort has been made for readers interested in path planning to fill the gap. Moreover, optimization techniques suitable for implementing ground, aerial, and underwater vehicles are also a part of this review. This paper covers the numerical, bio-inspired techniques and their hybridization with each other for each of the dimensions mentioned. The paper provides a consolidated platform, where plenty of available research on-ground autonomous vehicle and their trajectory optimization with the extension for aerial and underwater vehicles are documented

Coverage Optimization with a Dynamic Network of Drone Relays

The integration of aerial base stations carried by drones in cellular networks offers promising opportunities to enhance the connectivity enjoyed by ground users. In this paper, we propose an optimization framework for the 3-D placement and repositioning of a fleet of drones with a realistic inter-drone interference model and drone connectivity constraints. We show how to maximize network coverage by means of an extremal-optimization algorithm. The design of our algorithm is based on a mixed-integer non-convex program formulation for a coverage problem that is NP-Complete, as we prove in the paper. We not only optimize drone positions in a 3-D space in polynomial time, but also assign flight routes solving an assignment problem and using a strong geometrical tool, namely Bézier curves, which are extremely useful for non-uniform and realistic topologies. Specifically, we propose to fly drones following Bézier curves to seek the chance of approaching to clusters of ground users. This enhances coverage over time while users and drones move. We assess the performance of our proposal for synthetic scenarios as well as realistic maps extracted from the topology of a capital city. We demonstrate that our framework is near-optimal and using Bézier curves increases coverage up to 47 percent while drones move

Embracing drones and the Internet of drones systems in manufacturing – An exploration of obstacles

The manufacturing sector attributes the growing prominence of Drones and the Internet of Drones (IoD) systems to their multifaceted utility in delivery, process monitoring, infrastructure inspection, inventory management, predictive maintenance, and safety inspections. Despite their potential benefits, adopting these technologies faces significant obstacles that need systematic identification and resolution. The current literature inadequately addresses the barriers impeding the adoption of Drones and IoD systems in manufacturing, indicating a research gap. This study bridges this gap by providing comprehensive insights and facilitating the organisational transition towards embracing Drone and IoD technologies. This research identifies 20 critical barriers to deploying Drones and IoD in manufacturing. These barriers are validated through a global quantitative survey of 120 Drone experts and analysed via Exploratory Factor Analysis (EFA). EFA categorises these challenges into six distinct dimensions. Utilising the Analytical Hierarchy Process (AHP), these dimensions and individual barriers are ranked, incorporating feedback from five Drone specialists. The study highlights ‘Safety and Human Resource Barriers’ and ‘Payload Capacity and Battery Barriers’ as the most predominant obstacles. Key concerns include limited battery life, explosion risks, and potential damage to assets and individuals. This research significantly advances the existing literature by presenting a practical methodology for categorising and prioritising Drone and IoD adoption barriers. Employing EFA and AHP offers a globally relevant framework for stakeholders to strategically address these challenges, advancing the integration of drones and IoD systems in the manufacturing domain

A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future

A High Altitude Platform Station (HAPS) is a network node that operates in the stratosphere at an of altitude around 20 km and is instrumental for providing communication services. Precipitated by technological innovations in the areas of autonomous avionics, array antennas, solar panel efficiency levels, and battery energy densities, and fueled by flourishing industry ecosystems, the HAPS has emerged as an indispensable component of next-generations of wireless networks. In this article, we provide a vision and framework for the HAPS networks of the future supported by a comprehensive and state-of-the-art literature review. We highlight the unrealized potential of HAPS systems and elaborate on their unique ability to serve metropolitan areas. The latest advancements and promising technologies in the HAPS energy and payload systems are discussed. The integration of the emerging Reconfigurable Smart Surface (RSS) technology in the communications payload of HAPS systems for providing a cost-effective deployment is proposed. A detailed overview of the radio resource management in HAPS systems is presented along with synergistic physical layer techniques, including Faster-Than-Nyquist (FTN) signaling. Numerous aspects of handoff management in HAPS systems are described. The notable contributions of Artificial Intelligence (AI) in HAPS, including machine learning in the design, topology management, handoff, and resource allocation aspects are emphasized. The extensive overview of the literature we provide is crucial for substantiating our vision that depicts the expected deployment opportunities and challenges in the next 10 years (next-generation networks), as well as in the subsequent 10 years (next-next-generation networks).Comment: To appear in IEEE Communications Surveys & Tutorial

Military Innovation in the Third Age of U.S. Unmanned Aviation, 1991–2015

Military innovation studies have largely relied on monocausal accounts—rationalism, institutionalism, or culture—to explain technologically innovative and adaptive outcomes in defense organizations. None of these perspectives alone provided a compelling explanation for the adoption outcomes of unmanned aerial vehicles (UAVs) in the U.S. military from 1991 to 2015. Two questions motivated this research: Why, despite abundant material resources, mature technology, and operational need, are the most-capable UAVs not in the inventory across the services? What accounts for variations and patterns in UAV innovation adoption? The study selected ten UAV program episodes from the Air Force and Navy, categorized as high-, medium-, and low-end cases, for within-case and cross-case analysis. Primary and secondary sources, plus interviews, enabled process tracing across episodes. The results showed a pattern of adoption or rejection based on a logic-of-utility effectiveness and consistent resource availability: a military problem to solve, and a capability gap in threats or tasks and consistent monetary capacity; furthermore, ideational factors strengthened or weakened adoption. In conclusion, the study undermines single-perspective arguments as sole determinants of innovation, reveals that military culture is not monolithic in determining outcomes, and demonstrates that civil-military relationships no longer operate where civilian leaders hold inordinate sway over military institutions.Lieutenant Colonel, United States Air ForceApproved for public release; distribution is unlimited