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

Optimization for drone and drone-truck combined operations: A review of the state of the art and future directions

This paper presents a solution for the problem of minimum time coverage of ground areas using a group of unmanned air vehicles (UAVs) equipped with image sensors. The solution is divided into two parts: (i) the task modeling as a graph whose vertices are geographic coordinates determined in such a way that a single UAV would cover the area in minimum time; and (ii) the solution of a mixed integer linear programming problem, formulated according to the graph variables defined in the first part, to route the team of UAVs over the area. The main contribution of the proposed methodology, when compared with the traditional vehicle routing problem’s (VRP) solutions, is the fact that our method solves some practical problems only encountered during the execution of the task with actual UAVs. In this line, one of the main contributions of the paper is that the number of UAVs used to cover the area is automatically selected by solving the optimization problem. The number of UAVs is influenced by the vehicles’ maximum flight time and by the setup time, which is the time needed to prepare and launch a UAV. To illustrate the methodology, the paper presents experimental results obtained with two hand-launched, fixed-wing UAVs.

/pdf/multi-uav-routing-for-area-coverage-and-remote-sensing-with-374phkuyqh.pdf

Multi-UAV Routing for Area Coverage and Remote Sensing with Minimum Time.

https://www.tpbin.com/Uploads/Subjects/e09500b9-2256-4132-b3be-f6cb0b600a0d.pdf

Coverage path planning for UAVs based on enhanced exact cellular decomposition method

A level measurement system based on FMCW radar is developed. The structure of the measurement system is introduced. The methods of digital signal processing for the system are investigated. FFT algorithm is employed to process frequency difference in low-accuracy situation. When the signal-to-noise ratio is high, the high accuracy measurement is obtained by the AR spectral estimation. An autocorrelation filter is applied to the measurement system to reduce the disturbances. The resolution of the system which employs the methods of signal processing reaches 1 mm.

Digital Signal Processing for A Level Measurement System Based on FMCW Radar

This paper investigates the search probability and camera footprint of region coverage for UAVs Two kinds of search probability by using the UAV camera are proposed Moreover, the relationship between the UAV altitude and the camera footprint is also studied in this paper Some Formulars concerned with the UAV camera footprint are developed in two cases: flat flying and roll motion, and yaw motion The formulars can be used to obtain the length and width of the camera footprint and the coordinate transformation between the UAV centroid and the footprint center respectively Finally, the front-mounted angle of camera is discussed in this paper to ensure the region coverage more effective

Research on search probability and camera footprint of region coverage for UAVs

This paper proposes a new methodology to design a suboptimal H∞ dynamic output feedback control for singularly perturbed systems. A standard "singularly perturbed" closed-loop system is obtained by a permutation of the original closed-loop system. The controller is constructed in terms of solving a set of inequalities. An algorithm is given to solve those inequalities through iterative LMI (linear matrix inequality) formulation. An example demonstrates that the results are better than the standard time-scale decomposition method.

Suboptimal H 2 Static Output Feedback Control for Singularly Perturbed Systems

Molecular cloning and characterisation of the PmEglin cDNA in the leech Hirudinaria sp.

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