Flying ad-hoc network application scenarios and mobility models

[EN] Flying ad-hoc networks are becoming a promising solution for different application scenarios involving unmanned aerial vehicles, like urban surveillance or search and rescue missions. However, such networks present various and very specific communication issues. As a consequence, there are several research studies focused on analyzing their performance via simulation. Correctly modeling mobility is crucial in this context and although many mobility models are already available to reproduce the behavior of mobile nodes in an ad-hoc network, most of these models cannot be used to reliably simulate the motion of unmanned aerial vehicles. In this article, we list the existing mobility models and provide guidance to understand whether they could be actually adopted depending on the specific flying ad-hoc network application scenarios, while discussing their advantages and disadvantages.Bujari, A.; Tavares De Araujo Cesariny Calafate, CM.; Cano, J.; Manzoni, P.; Palazzi, CE.; Ronzani, D. (2017). Flying ad-hoc network application scenarios and mobility models. International Journal of Distributed Sensor Networks. 13(10):1-17. doi:10.1177/1550147717738192S117131

Space-Air-Ground Integrated 6G Wireless Communication Networks: A Review of Antenna Technologies and Application Scenarios

A review of technological solutions and advances in the framework of a Vertical Heterogeneous Network (VHetNet) integrating satellite, airborne and terrestrial networks is presented. The disruptive features and challenges offered by a fruitful cooperation among these segments within a ubiquitous and seamless wireless connectivity are described. The available technologies and the key research directions for achieving global wireless coverage by considering all these layers are thoroughly discussed. Emphasis is placed on the available antenna systems in satellite, airborne and ground layers by highlighting strengths and weakness and by providing some interesting trends in research. A summary of the most suitable applicative scenarios for future 6G wireless communications are finally illustrated

Task-driven multi-formation control for coordinated UAV/UGV ISR missions

The report describes the development of a theoretical framework for coordination and control of combined teams of UAVs and UGVs for coordinated ISR missions. We consider the mission as a composition of an ordered sequence of subtasks, each to be performed by a different team. We design continuous cooperative controllers that enable each team to perform a given subtask and we develop a discrete strategy for interleaving the action of teams on different subtasks. The overall multi-agent coordination architecture is captured by a hybrid automaton, stability is studied using Lyapunov tools, and performance is evaluated through numerical simulations

Towards Robust UAV Tracking in GNSS-Denied Environments: A Multi-LiDAR Multi-UAV Dataset

With the increasing prevalence of drones in various industries, the navigation and tracking of unmanned aerial vehicles (UAVs) in challenging environments, particularly GNSS-denied areas, have become crucial concerns. To address this need, we present a novel multi-LiDAR dataset specifically designed for UAV tracking. Our dataset includes data from a spinning LiDAR, two solid-state LiDARs with different Field of View (FoV) and scan patterns, and an RGB-D camera. This diverse sensor suite allows for research on new challenges in the field, including limited FoV adaptability and multi-modality data processing. The dataset facilitates the evaluation of existing algorithms and the development of new ones, paving the way for advances in UAV tracking techniques. Notably, we provide data in both indoor and outdoor environments. We also consider variable UAV sizes, from micro-aerial vehicles to more standard commercial UAV platforms. The outdoor trajectories are selected with close proximity to buildings, targeting research in UAV detection in urban areas, e.g., within counter-UAV systems or docking for UAV logistics. In addition to the dataset, we provide a baseline comparison with recent LiDAR-based UAV tracking algorithms, benchmarking the performance with different sensors, UAVs, and algorithms. Importantly, our dataset shows that current methods have shortcomings and are unable to track UAVs consistently across different scenarios

A survey of urban drive-by sensing: An optimization perspective

Pervasive and mobile sensing is an integral part of smart transport and smart city applications. Vehicle-based mobile sensing, or drive-by sensing (DS), is gaining popularity in both academic research and field practice. The DS paradigm has an inherent transport component, as the spatial-temporal distribution of the sensors are closely related to the mobility patterns of their hosts, which may include third-party (e.g. taxis, buses) or for-hire (e.g. unmanned aerial vehicles and dedicated vehicles) vehicles. It is therefore essential to understand, assess and optimize the sensing power of vehicle fleets under a wide range of urban sensing scenarios. To this end, this paper offers an optimization-oriented summary of recent literature by presenting a four-step discussion, namely (1) quantifying the sensing quality (objective); (2) assessing the sensing power of various fleets (strategic); (3) sensor deployment (strategic/tactical); and (4) vehicle maneuvers (tactical/operational). By compiling research findings and practical insights in this way, this review article not only highlights the optimization aspect of drive-by sensing, but also serves as a practical guide for configuring and deploying vehicle-based urban sensing systems.Comment: 24 pages, 3 figures, 4 table

Multi-UAV Integrated Internet of Things System for Generating Safe Map in Post-Disaster

芝浦工業大学2019年

UAS Path Planning for Dynamical Wildfire Monitoring with Uneven Importance

Unmanned Aircraft Systems (UASs) offer many benefits in wildfire monitoring when compared to traditional wildfire monitoring technologies. When planning the path of an UAS for wildfire monitoring, it is important to consider the uneven propagation nature of the wildfire because different parts of the fire boundary demand different levels of monitoring attention (importance) based on the propagation speed. In addition, many of the existing works adopt a centralized approach for the path planning of the UASs. However, the use of centralized approaches is often limited in terms of applicability and adaptability. This work focuses on developing decentralized UAS path planning algorithms to autonomously monitor a spreading wildfire considering uneven importance. The algorithms allow the UASs to focus on the most active regions of a wildfire while still covering the entire fire perimeter. When monitoring a relatively smaller and spatially static fire, a single UAS might be adequate for the task. However, when monitoring a larger wildfire that is evolving dynamically in space and time, efficient and optimized use of multiple UASs is required. Based on this need, we also focus on decentralized and importance-based multi-UAS path planning for wildfire monitoring. The design, implementation, analysis, and simulation results have been discussed in details for both single-UAS and multi-UAS path planning algorithms. Experiment results show the effectiveness and robustness of the proposed algorithms for dynamic wildfire monitoring