An autonomous system has been widely applied for various civil/military research because of its versatile capability of understanding high-level intent and direction of a surrounding environment and targets of interest. However, as autonomous systems can be out of control to cause serious loss, injury, or death in the worst case, the verification of their functionalities has got increasing attention. For that reason, this study is focused on the verification of a heterogeneous multi-agent autonomous system. The thesis first presents an overview of formal methods, especially focuses on model checking for autonomous systems verification. Then, six case studies are presented to verify the decision making behaviours of multi-agent system using two basic scenarios: surveillance and convoy. The initial system considered in the surveillance mission consists of a ground control system and a micro aerial vehicle. Their decision-making behaviours are represented by means of Kripke model and computational tree logic is used to specify the properties of this system. For automatic verification, MCMAS (Model Checker for Multi-Agent Systems) is adopted due to its novel capability to accommodate the multi-agent system. After that, the initial system is extended to include a substitute micro aerial vehicle. These initial case studies are then further extended based on SEAS DTC exemplar 2 dealing with behaviours of convoy protection. This case study includes now a ground control system, an unmanned aerial vehicle, and an unmanned ground vehicle. The MCMAS successfully verifies the targeting behaviours of the team-level unmanned systems. Reversely, these verification results help retrospectively improve the design of decision-making algorithms by considering additional agents and behaviours during four steps of scenario modification. Consequently, the last scenario deals with the system composed of a ground control system, two unmanned aerial vehicles, and four unmanned ground vehicles with fault-tolerant and communications relay capabilities. In conclusion, this study demonstrates the feasibility of model checking algorithms as a verification tool of a multi-agent system in an initial design stage. Moreover, this research can be an important first step of the certification of multi-agent autonomous systems for the domains of robotics, aerospace and aeronautics.

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Approved for public release; distribution is unlimited. / An autonomously guided rocket-powered delivery vehicle has been under development at the Naval Postgraduate School. Designed to eventually counter UAV swarm attacks, the vehicle made advances toward reaching a target in the sky. These advances reduced the time needed to launch, modify, and relaunch the rocket, while adding capabilities such as data transfer along the vehicle axis and the rapid download of flight data. Improving the vehicle included reconfiguring the guidance, navigation, and control (GNC) strategy. Advancements included the design, implementation, and evaluation of electronic servo control, actuating fins, and the mechanical coupling design. The forward compartment in the vehicle’s nose cone was structurally modified for the GNC equipment and to support electronics under high-g launch conditions. Modifications included innovative designs for managing heat transfer requirements. Using off-the-shelf subsystem components kept the advancements fiscally mindful. After implementing the design features, two final test launches were performed: one demonstrated a control spin rate of 8.5 rad/sec; the other showed the vehicle’s ability to execute pitch maneuvers on a single axis. The test results can be used to improve the GNC software and servo control parameters. Continued development will allow the system to become a viable option for countering UAV swarms. / Ensign, United States Navy

International drone goods transportation - Abstract, key words The aim of this work is to explore the possibilities of liability concepts in relation to unmanned aerial vehicles that transport goods in the international transport of goods. For this purpose, a comparison of the normative theory of František Weyr and the way of functioning of formally logical systems is performed within the work. This normative theory has a great impact on the actual functioning of the information system itself, which is exempt from the content of its own rule contained in the norm itself. There are described methods of acknowledging machines and the method of interpretation and application of individual rules contained in norms themselves that are being interpreted by these machines. All this precisely with regard to the fact that unmanned aerial vehicles cannot learn to distinguish between inner values of norms, on which individual legal norms are based. This is because unmanned aerial vehicles cannot achieve this with the help of a tool of pure intelligence alone. Since unmanned aerial vehicles interpret and apply their own internal norms to the outside world only as they are set within their normative setting. This normative setting is also related to the protection against banal evil and the protection of notional...

The ever-increasing demand for better mobile experiences is propelling the research communities to look ahead at how future networks can be geared up to meet such demands. It is likely that the next-generation of wireless communications will be revolutionary, outpacing the current systems capabilities in terms connectivity, reliability and intelligence. These trends and predictions will cause a revolutionary change in the wireless communications. In this context, the concept of Ultra-Dense Network (UDN) is poised to be the cornerstone of the development of fifth generation(5G) systems, whereby a massive number of base stations (BSs) are deployed for enhancing the network performance metrics. Though such densification might be economically viable in urban areas, it is mostly unfavorable in rural ones due to the sheer complexity and the various factors involved the planning and installation processes; all of which trigger the need for cost-effective, flexible and easily-implementable solutions. As a result, unmanned aerial vehicles (UAVs) emerge as a promising alternative solution for enhancing wireless coverage. Due to their mobility capabilities, UAVs are of particular importance in events of (i) terrestrial-based cellular systems dilapidation, (ii) infrastructure absence in remote and suburban areas, or (iii) limited-duration events or activities wherein there is a short-term need for supplementary network resources to handle the overload. While a growing body literature works towards characterizing and providing insights into the performance of UAVs-only networks (serving the first two purposes), understanding the performance of such networks when coupled with existing terrestrial BSs remains a challenging, yet interesting, open research venue. Towards this direction, this thesis provides a rigorous analysis of the downlink coverage probability of hybrid aerial-terrestrial networks using tools from Stochastic Geometry. The thesis presents a mathematical model that characterizes the coverage probability metric under different network environments. The proposed model is validated against intensive simulations so as to substantiate the analytical results. The developed work is essential to understanding the premises of one possible solution to the UDNs of tomorrow, capture its key performance metrics and, most importantly, to uncover key design insights and reveal new directions for the wireless communication industry.

Hurricane Isaac’s landfall on the coast of Louisiana spawned a hydrological research project between Mississippi State University (MSU), the Northern Gulf Institute (NGI), and the National Oceanic and Atmospheric Administration (NOAA) in the Lower Pearl River Basin (LPRB). Unmanned aerial systems data collection missions were scheduled every two months in the LPRB. This research provides a comparison between Landsat-8 imagery and corresponding UAS imagery with regards to the four remote sensing resolutions: spatial, spectral, radiometric, and temporal. Near-infrared (NIR) imagery from each platform was compared by land-water masks and statistical comparisons. A classification method known as natural breaks with Jenks Optimization determined threshold values between land and water for each image. Land-water masks revealed substantial differences between areas of land and water in comparing imagery. The overall difference in average land and water percentages between the two platforms was 1.77%; however, a larger percentage was 20.41% in a single comparison.

Unmanned air vehicles have been increasing in their autonomous capabilities. This research furthers these capabilities by focusing on the automation of landing site determination for rotorcraft in urban environments. Automated landing saves energy and allows the aircraft to choose areas that are safe for people and the aircraft. Two methods are used to gather information about the terrain of potential landing sites. One method is 3D reconstruction from multiple camera images. The other method uses a range sensor to reconstruct the terrain. Both of these methods create an inertial terrain map of the environment in the form of a point cloud that can be investigated for possible landing sites. Two strategies were developed to search the terrain map for possible landing sites: grid-based RANSAC and Recursive-RANSAC (R-RANSAC). Both strategies search for flat stable areas for landing. Grid-based RANSAC separates the terrain map into discrete portions for plane fitting analysis. These fitted planes are used to determine whether portions of the terrain map are suitable for landing. Two additional variations of grid-based RANSAC were explored that resulted in improvements to the approach. This strategy can quickly find landing sites from large terrain maps. The other strategy, R-RANSAC, is a recursive approach that analyzes each point in the terrain map for plane fitting. New planes are created as needed to fit points in the terrain map. Planes that fit a large number of points are analyzed for possible landing locations. This strategy is more complex to implement, but results in a simpler model of the environment: a small set of 3D planes. The results are displayed with the possible landing locations. Both landing-site strategies were implemented onboard a hexrotor aircraft and successfully demonstrated in flight.

Unmanned air vehicles (UAVs) are attracting increased attention as their envelope of suitable tasks expands to include activities such as perimeter tracking, search and rescue assistance, surveillance and reconnaissance. The simplified goal of many of these tasks is to image an object for tracking or information-gathering purposes. The ability to determine the inertial location of a visible, ground-based object without requiring a priori knowledge of its exact location would therefore prove beneficial. This thesis discusses a method of localizing a ground-based object when imaged from a fixed-wing UAV. Using the target's pixel location in an image, with measurements of UAV position, attitude and camera pose angles, the target is localized in world coordinates. This thesis also presents a study of possible error sources and localization sensitivities to each source. From this study, an accuracy within 15.5 m of actual target location is expected. Also, several methods of filtering are presented, which allow for effective noise reduction. Finally, filtered hardware results are presented that verify these expectations by localizing a target from a fixed-wing UAV using on-board vision to within 10.9 meters.

Coalitions are collections of agents that join together to solve a common problem that either cannot be solved individually or can be solved more efficiently as a group. Each individual agent has capabilities that can benefit the group when working together as a coalition. Typically, individual capabilities are joined together in an additive way when forming a coalition. This work will introduce a new operator that is used when combining capabilities, and suggest that the behavior of the operator is contextual, depending on the nature of the capability itself. This work considers six different capabilities of Unmanned Air Vehicles (UAV) and determines the nature of the new operator in the context of each capability as coalitions (squadrons) of UAVs are formed. Coalitions are formed using three different search algorithms, both with and without heuristics: Depth-First, Depth-First Iterative Deepening, and Genetic Algorithm (GA). The effectiveness of each algorithm is evaluated. Multi agent-based UAV simulation software was developed and used to test the ideas presented. In addition to coalition formation, the software aims to address additional multi-agent issues such as agent identity, mutability, and communication as applied to UAV systems, in a realistic simulated environment. Social potential fields provide a means of modeling a clustering attractive force at the same time as a collision-avoiding repulsive force, and are used by the simulation to maintain aircraft position relative to other UAVs.

<p> In this thesis, we address the problem of sensor management with particular application to using unmanned aerial vehicles (U AV s) for multi target tracking. Also, we present a decision based approach for controlling information flow in decentralized multi-target multi-sensor data fusion.</p> <p> Considering the problem of sensor management for multitarget tracking, we study the problem of decision based control of a group of UAVs carrying out surveillance over a region that includes a number of moving targets. The objective is to maximize the information obtained and to track as many targets as possible with the maximum possible accuracy. Uncertainty in the information obtained by each UAV regarding the location of the ground targets are addressed in the problem formulation. We propose an altered version of a classical Value Iteration algorithm, one of the most commonly used techniques to calculate the optimal policy for Markov Decision Processes (MDPs) based on Dynamic Element Matching (DEM) algorithms. DEM algorithms, widely used for reducing harmonic distortion in Digital-to-Analog converters, are used as a core element in the modified algorithm. We introduce and demonstrate a number of new performance metrics, to verify the effectiveness of an MDP policy, especially useful for quantifying the impact of the modified DEM-based Value Iteration algorithm on an MDP policy. Also, we introduce a multi-level hierarchy of MDPs controlling each of the UAV s. Each level in the hierarchy solves a problem at a different level of abstraction. Simulation results are presented on a representative multisensor-multitarget tracking problem showing a significant improvement in performance compared to the classical algorithm. The proposed method demonstrated robust performance while guaranteeing polynomial computational complexity.</p> <p> Decentralized multisensor-multitarget tracking has numerous advantages over singlesensor or single-platform tracking. In this thesis, we present a solution for one of the main problems in decentralized tracking, namely, distributed information transfer and fusion among the participating platforms. We present a decision mechanism for collaborative distributed data fusion that provides each platform with the required data for the fusion process while substantially reducing redundancy in the information flow in the overall system. We consider a distributed data fusion system consisting of platforms that are decentralized, heterogenous, and potentially unreliable. The proposed approach, which is based on Markov Decision Processes with introduced hierarchial structure will control the information exchange and data fusion process. The information based objective function is based on the Posterior Cramer-Rao lower bound and constitutes the basis of a reward structure for Markov decision processes which are used, together with decentralized lookup substrate, to control the data fusion process. We analyze three distributed data fusion algorithms - associated measurement fusion, tracklet fusion and track-to-track fusion. The thesis also provides a detailed analysis of communication and computational load in distributed tracking algorithms. Simulation examples demonstrate the operation and the performance results of the system.</p> <p> In this thesis, we also present the development of a multisensor-multitarget tracking testbed for simulating large-scale distributed scenarios, capable of handling multiple, heterogeneous sensors, targets and data fusion methods</p>. / Thesis / Doctor of Philosophy (PhD)