Applying Tabu Heuristic to Wind Influenced, Minimum Risk and Maximum Expected Coverage Routes

The purpose of this thesis is to provide Air Combat Command a method for determining the number of predator unmanned aerial vehicles (UAVs) required to cover a pre-selected target. Extending previous research that employs reactive TABU search methods for deterministic vehicle routing problems, this thesis incorporates wind effects that can significantly alter the travel times for any given scenario. Additionally, it accounts for possible attrition by introducing minimum risk route and expected number of target covered to the objective function. The results of the TABU search and subsequent Monte-Carlo simulation: gives the number of predator\u27s required to cover a target set, identifies \u27robust\u27 routes, and suggests routes that increase expected number of targets covered while reducing losses

Air Force Institute of Technology Research Report 1999

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, and Engineering Physics

Technology challenges of stealth unmanned combat aerial vehicles

The ever-changing battlefield environment, as well as the emergence of global command and control architectures currently used by armed forces around the globe, requires the use of robust and adaptive technologies integrated into a reliable platform. Unmanned Combat Aerial Vehicles (UCAVs) aim to integrate such advanced technologies while also increasing the tactical capabilities of combat aircraft. This paper provides a summary of the technical and operational design challenges specific to UCAVs, focusing on high-performance, and stealth designs. After a brief historical overview, the main technology demonstrator programmes currently under development are presented. The key technologies affecting UCAV design are identified and discussed. Finally, this paper briefly presents the main issues related to airworthiness, navigation, and ethical concerns behind UAV/UCAV operations

İNSANSIZ HAVA SİSTEMLERİ ROTA PLANLAMASI DİNAMİK ÇÖZÜM METOTLARI VE LİTERATÜR ARAŞTIRMASI

War tools and materials, which are an indicator of war strategy and development, vary with the technology. Modern Warfares in the information age, where near space and the space being used as a tool, differ from both the agricultural era wars, in which arrows and bows had been used as a tool, and industrial era battles, in which machine guns and tanks were employed. These characteristics influence this area of interest and area of influence in the area of responsibilities, and affect the ability and the necessity of modern armies as well. Being able to perform reconnaissance and surveillance missions in the most effective and efficient way is reliant on not only having the knowledge to create and invent them as well as having them in the inventor but also the ability of planning these systems with a modern scientific approach. Vehicle Routing Problem (VRP), encountered during the assignment of Unmanned Aerial Systems\Vehicles (UAS\V) which is being used at the strategic level, can lead to elevated costs in the defense sector as well as other sectors. For this reason, the efficient solution of route planning is a very important issue to provide major cost savings and to observe the targets timely.This study investigates the literature in “dynamic” route planning “solution” methods and defines the approaches for future “dynamic solution” studies of strategic UAVs which are being recently used in Turkey. Using this approach will increase the efficiency of usage of the UAVs and decrease the operating and project costs of them as well.Savaş stratejisinin bir göstergesi olan muharebe araç ve gereçleri, teknoloji ile birlikte değişiklik göstermektedir. Yakın uzay ve uzayın da bir araç olarak kullanıldığı bilgi çağının savaşları; ok ve yayın kullanıldığı tarım dönemi ile top ve tüfeklerin kullanıldığı sanayi dönemi savaşlarından farklılık göstermektedir. Bu farklılıklar, harekât bölgesinin etki ve ilgi alanını genişlettiği gibi modern orduların kabiliyetlerini ve gereksinimlerini de etkilemektedir. Keşif ve gözetleme görevinin en etkin ve verimli şekilde yapabilmesi, envanterindeki sistemlerin modern olması ile birlikte bu sistemleri bilimsel yaklaşımlarla planlayabilme yeteneğine bağlıdır. Stratejik seviyede kullanılan İnsansız Hava Araçlarının (İHA) görevlendirmeleri esnasında karşılaşılan Araç Rotalama Problemleri (ARP), diğer sektörlerde olduğu gibi savunma sektöründe de oldukça yüksek maliyetlere sebep olabilmektedir. Bu nedenle İHA rota planlamalarının verimli bir şekilde çözümü, büyük tasarruflar sağlayacak olması ve hedeflerin zamanında gözetlenebilmeleri açısından önemlidir. Bu çalışmanın amacı, İnsansız Hava Sistemlerinin (İHS) dinamik rota planlamasına yönelik yapılan çalışmalarının incelenmesi ve ileride yapılabilecek çözüm yaklaşımlarına yön verilmesidir. Bu sayede, Türkiye’de henüz kullanılmaya başlayan stratejik İHS’lerin görev etkinliklerinin artırılması, proje ve kullanım maliyetlerinin düşürülmesi hedeflenmektedir

Heterogeneous mission planning for a single unmanned aerial vehicle (UAV) with attention-based deep reinforcement learning

Large-scale and complex mission environments require unmanned aerial vehicles (UAVs) to deal with various types of missions while considering their operational and dynamic constraints. This article proposes a deep learning-based heterogeneous mission planning algorithm for a single UAV. We first formulate a heterogeneous mission planning problem as a vehicle routing problem (VRP). Then, we solve this by using an attention-based deep reinforcement learning approach. Attention-based neural networks are utilized as they have powerful computational efficiency in processing the sequence data for the VRP. For the input to the attention-based neural networks, the unified feature representation on heterogeneous missions is introduced, which encodes different types of missions into the same-sized vectors. In addition, a masking strategy is introduced to be able to consider the resource constraint (e.g., flight time) of the UAV. Simulation results show that the proposed approach has significantly faster computation time than that of other baseline algorithms while maintaining a relatively good performance

Air Force Institute of Technology Research Report 2000

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, and Engineering Physics

The In-Transit Vigilant Covering Tour Problem of Routing Unmanned Ground Vehicles

The routing of unmanned ground vehicles for the surveillance and protection of key installations is modeled as a new variant of the Covering Tour Problem (CTP). The CTP structure provides both the routing and target sensing components of the installation protection problem. Our variant is called the in-transit Vigilant Covering Tour Problem (VCTP) and considers not only the vertex cover but also the additional edge coverage capability of the unmanned ground vehicle while sensing in-transit between vertices. The VCTP is formulated as a Traveling Salesman Problem (TSP) with a dual set covering structure involving vertices and edges. An empirical study compares the performance of the VCTP against the CTP on test problems modified from standard benchmark TSP problems to apply to the VCTP. The VCTP performed generally better with shorter tour lengths but at higher computational cost

A Tandem Drone-ground Vehicle for Accessing Isolated Locations for First Aid Emergency Response in Case of Disaster

The collapse of infrastructures is very often a complicating factor for the early emergency actuations after a disaster. A proper plan to better cover the needs of the affected people within the disaster area while maintaining life-saving relief operations is mandatory hence. In this paper, we use a drone for flying over a set of difficult-to-access locations for imaging issues to get information to build a risk assessment as the earliest stage of the emergency operations. While the drone provides the flexibility required to visit subsequently a sort of isolated locations, it needs a commando vehicle in ground for (i) monitoring the deployment of operations and (ii) being a recharging station where the drone gets fresh batteries. This work proposes a decision-making process to plan the mission, which is composed by the ground vehicle stopping points and the sequence of locations visited for each drone route. We propose a Genetic Algorithm (GA) which has proven to be helpful in finding good solutions in short computing times. We provide experimental analysis on the factors effecting the performance of the output solutions, around an illustrative test instance. Results show the applicability of these techniques for providing proper solutions to the studied problem