The rapid growth of consumer unmanned aerial vehicles (UAVs) is creating promising new business opportunities for cellular operators On the one hand, UAVs can be connected to cellular networks as new types of user equipment, therefore generating significant revenues for the operators that can guarantee their stringent service requirements On the other hand, UAVs offer the unprecedented opportunity to realize UAV-mounted flying base stations (BSs) that can dynamically reposition themselves to boost coverage, spectral efficiency, and user quality of experience Indeed, the standardization bodies are currently exploring possibilities for serving commercial UAVs with cellular networks Industries are beginning to trial early prototypes of flying BSs or user equipments, while academia is in full swing researching mathematical and algorithmic solutions to address interesting new problems arising from flying nodes in cellular networks In this paper, we provide a comprehensive survey of all of these developments promoting smooth integration of UAVs into cellular networks Specifically, we survey: 1) the types of consumer UAVs currently available off-the-shelf; 2) the interference issues and potential solutions addressed by standardization bodies for serving aerial users with the existing terrestrial BSs; 3) the challenges and opportunities for assisting cellular communications with UAV-based flying relays and BSs; 4) the ongoing prototyping and test bed activities; 5) the new regulations being developed to manage the commercial use of UAVs; and 6) the cyber-physical security of UAV-assisted cellular communications

Survey on UAV Cellular Communications: Practical Aspects, Standardization Advancements, Regulation, and Security Challenges

Unmanned aerial vehicles (UAVs), or aerial drones, are an emerging technology with significant market potential. UAVs may lead to substantial cost savings in, for instance, monitoring of difficult-to-access infrastructure, spraying fields and performing surveillance in precision agriculture, as well as in deliveries of packages. In some applications, like disaster management, transport of medical supplies, or environmental monitoring, aerial drones may even help save lives. In this article, we provide a literature survey on optimization approaches to civil applications of UAVs. Our goal is to provide a fast point of entry into the topic for interested researchers and operations planning specialists. We describe the most promising aerial drone applications and outline characteristics of aerial drones relevant to operations planning. In this review of more than 200 articles, we provide insights into widespread and emerging modeling approaches. We conclude by suggesting promising directions for future research.

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

Path planning techniques for unmanned aerial vehicles: A review, solutions, and challenges

Coverage path planning consists of finding the route which covers every point of a certain area of interest. In recent times, Unmanned Aerial Vehicles (UAVs) have been employed in several application domains involving terrain coverage, such as surveillance, smart farming, photogrammetry, disaster management, civil security, and wildfire tracking, among others. This paper aims to explore and analyze the existing studies in the literature related to the different approaches employed in coverage path planning problems, especially those using UAVs. We address simple geometric flight patterns and more complex grid-based solutions considering full and partial information about the area of interest. The surveyed coverage approaches are classified according to a classical taxonomy, such as no decomposition, exact cellular decomposition, and approximate cellular decomposition. This review also contemplates different shapes of the area of interest, such as rectangular, concave and convex polygons. The performance metrics usually applied to evaluate the success of the coverage missions are also presented.

Survey on Coverage Path Planning with Unmanned Aerial Vehicles

The rapid growth of consumer Unmanned Aerial Vehicles (UAVs) is creating promising new business opportunities for cellular operators. On the one hand, UAVs can be connected to cellular networks as new types of user equipment, therefore generating significant revenues for the operators that can guarantee their stringent service requirements. On the other hand, UAVs offer the unprecedented opportunity to realize UAV-mounted flying base stations that can dynamically reposition themselves to boost coverage, spectral efficiency, and user quality of experience. Indeed, the standardization bodies are currently exploring possibilities for serving commercial UAVs with cellular networks. Industries are beginning to trial early prototypes of flying base stations or user equipments, while academia is in full swing researching mathematical and algorithmic solutions to address interesting new problems arising from flying nodes in cellular networks. In this article, we provide a comprehensive survey of all of these developments promoting smooth integration of UAVs into cellular networks. Specifically, we survey (i) the types of consumer UAVs currently available off-the-shelf, (ii) the interference issues and potential solutions addressed by standardization bodies for serving aerial users with the existing terrestrial base stations, (iii) the challenges and opportunities for assisting cellular communications with UAV-based flying relays and base stations, (iv) the ongoing prototyping and test bed activities, (v) the new regulations being developed to manage the commercial use of UAVs, and (vi) the cyber-physical security of UAV-assisted cellular communications.

Focus is on the coverage path planning problem with UAV for 3D terrain reconstruction.The aim is to obtain a path that reduces the battery consumption, minimizing the turns.Our algorithm deals with both convex and non-convex regionsThe algorithm can perform the coverage when complex regions are considered.Can achieve better solutions than a previous result (using less turns). Three-dimensional terrain reconstruction from 2D aerial images is a problem of utmost importance due its wide level of applications. It is relevant in the context of intelligent systems for disaster managements (for example to analyze a flooded area), soil analysis, earthquake crisis, civil engineering, urban planning, surveillance and defense research.It is a two level problem, being the former the acquisition of the aerial images and the later, the 3D reconstruction. We focus here in the first problem, known as coverage path planning, and we consider the case where the camera is mounted on an unmanned aerial vehicle (UAV).In contrast with the case when ground vehicles are used, coverage path planning for a UAV is a lesser studied problem. As the areas to cover become complex, there is a clear need for algorithms that will provide good enough solutions in affordable times, while taking into account certain specificities of the problem at hand. Our algorithm can deal with both convex and non-convex areas and their main aim is to obtain a path that reduces the battery consumption, through minimizing the number of turns.We comment on line sweep calculation and propose improvements for the path generation and the polygon decomposition problems such as coverage alternatives and the interrupted path concept. Illustrative examples show the potential of our algorithm in two senses: ability to perform the coverage when complex regions are considered, and achievement of better solution than a published result (in terms of the number of turns used).

Coverage path planning with unmanned aerial vehicles for 3D terrain reconstruction

PRoA: An intelligent multi-criteria Personalized Route Assistant

The result of a multiobjective or a many-objective optimization problem is a large set of non-dominated solutions. Once the Pareto Front (or a good approximation of it) has been found, then providing the decision maker with a smaller set of “interesting solutions” is a key step. Here, the focus is on how to select such a set of solutions of interest which, in contrast to previous approaches that relied on geometrical features, is carried out considering the decision maker’s preferences. The proposed a posteriori approach consists in assigning an interval of potential scores to every solution, where such scores depend on the decision maker’s preferences. The solutions are then compared and filtered according to their corresponding intervals, using a recently proposed possibility degree formula. Three examples, with two, three and many objectives are used to show the benefits of the proposal.

An approach to identify solutions of interest from multi and many-objective optimization problems

The Personalized Route Problem with fuzzy constraints deals with the problem of finding a set of routes according to the users’s preferences. The solutions are obtained solving a set of problems associated with different α-cuts. However, under different α values unique solutions are not guaranteed, being possible to obtain a set of duplicated solutions, which is not desirable.Here we propose a method to reduce the number of equal solutions focusing on solving specific α-cuts, thus avoiding other ones that will obtain a duplicated solution. Two examples are shown to illustrate the proposal.

A New Approach for Solving Personalized Routing Problems with Fuzzy Constraints

The Personalized Route Problem resembles the so-called multi-criteria Shortest Path Problem where every arc (street) of the graph (map) has a set of costs (values) associated to a set of criteria (features). The personalization of the path comes when the user a) determines how important is each criterion according to personal preferences and b) indicates constraints on the criteria values. The preferences are often uncertain, imprecise or inexact. Also, it seems reasonable to allow some relaxation on the constraints. We propose and define a new model for the Personalized Route Problem with fuzzy constraints. As an example, we show its application to the Shortest Path Route with fuzzy constraints on the slopes values.

Marina Torres

Papers

Coverage path planning with unmanned aerial vehicles for 3D terrain reconstruction

PRoA: An intelligent multi-criteria Personalized Route Assistant

An approach to identify solutions of interest from multi and many-objective optimization problems

A New Approach for Solving Personalized Routing Problems with Fuzzy Constraints

Personalized route problem with fuzzy constraints