Autonomous three-dimensional formation flight for a swarm of unmanned aerial vehicles

This paper investigates the development of a new guidance algorithm for a formation of unmanned aerial vehicles. Using the new approach of bifurcating potential fields, it is shown that a formation of unmanned aerial vehicles can be successfully controlled such that verifiable autonomous patterns are achieved, with a simple parameter switch allowing for transitions between patterns. The key contribution that this paper presents is in the development of a new bounded bifurcating potential field that avoids saturating the vehicle actuators, which is essential for real or safety-critical applications. To demonstrate this, a guidance and control method is developed, based on a six-degreeof-freedom linearized aircraft model, showing that, in simulation, three-dimensional formation flight for a swarm of unmanned aerial vehicles can be achieved

Using Agent-Based Modeling to Evaluate UAS Behaviors in a Target-Rich Environment

The trade-off between accuracy and speed is a re-occurring dilemma in many facets of military performance evaluation. This is an especially important issue in the world of ISR. One of the most progressive areas of ISR capabilities has been the utilization of Unmanned Aircraft Systems (UAS). Many people believe that the future of UAS lies in smaller vehicles flying in swarms. We use the agent-based System Effectiveness and Analysis Simulation (SEAS) to create a simulation environment where different configurations of UAS vehicles can process targets and provide output that allows us to gain insight into the benefits and drawbacks of each configuration. Our evaluation on the performance of the different configurations is based on probability of correct identification, average time to identify a target after it has deployed in the area of interest, and average time to identify all targets in an area

Trajectory Optimization of Meteorological Sampling

Swarming involves controlling multiple unmanned aerial systems or UAS in formation through the use of controls and algorithms. Swarm systems may be distributed and not rely on a central controller. As a result, this gives the system the potential to be robust and scalable, allowing for flexibility for the engineers to approach problems differently. Based on a variety of a few models and algorithms, such as artificial potential fields (APFs), agent-based modeling, dynamic data driven application systems (DDDAS), and virtual structures, it may be determined that using a variation of one of these would be the best course of action for formation flight for a swarm of UASs. Choosing the right controller is dependent on what works best for acquiring atmospheric data in a coordinated formation. Current atmospheric data is commonly taken using a weather tower or mesonet. A mesonet is typically a 10m high tower with a pressure, temperature, humidity sensor placed at the top. Deciding which controller can be used to not only take useful atmospheric data, but in many cases replace a mesonet due to mobility and customization is the goal. A wind profile is a transient matter, so using a swarm vs using one drone or a mesonet helps to solve the issues that the latter two run into due to time and space. A swarm can record multiple points at one time due to each agent being a data point representation, whereas a single drone can only account for a single location in time. A swarm using a virtual structure (VS) can cover a variety of amounts of space in a coordinated shape. A meosnet is stationary and only oriented vertically and an uncoordinated group of UAS does not have the capability to operate together. This leaves the capability that a VS swarm has to fill in the gaps or even replace the traditional approaches. An array of sensor packages with mobility, coordinated movement, and endless data points could give the VS swarm the advantage in atmospheric data sampling

An OpenEaagles Framework Extension for Hardware-in-the-Loop Swarm Simulation

Unmanned Aerial Vehicle (UAV) swarm applications, algorithms, and control strategies have experienced steady growth and development over the past 15 years. Yet, to this day, most swarm development efforts have gone untested and thus unimplemented. Cost of aircraft systems, government imposed airspace restrictions, and the lack of adequate modeling and simulation tools are some of the major inhibitors to successful swarm implementation. This thesis examines how the OpenEaagles simulation framework can be extended to bridge this gap. This research aims to utilize Hardware-in-the-Loop (HIL) simulation to provide developers a functional capability to develop and test the behaviors of scalable and modular swarms of autonomous UAVs in simulation with high confidence that these behaviors will prop- agate to real/live ight tests. Demonstrations show the framework enhances and simplifies swarm development through encapsulation, possesses high modularity, pro- vides realistic aircraft modeling, and is capable of simultaneously accommodating four hardware-piloted swarming UAVs during HIL simulation or 64 swarming UAVs during pure simulation

Effects of Dynamically Weighting Autonomous Rules in a UAS Flocking Model

Within the U.S. military, senior decision-makers and researchers alike have postulated that vast improvements could be made to current Unmanned Aircraft Systems (UAS) Concepts of Operation through inclusion of autonomous flocking. Myriad methods of implementation and desirable mission sets for this technology have been identified in the literature; however, this thesis posits that specific missions and behaviors are best suited for autonomous military flocking implementations. Adding to Craig Reynolds\u27 basic theory that three naturally observed rules can be used as building blocks for simulating flocking behavior, new rules are proposed and defined in the development of an autonomous flocking UAS model. Simulation validates that missions of military utility can be accomplished in this method through incorporation of dynamic event- and time-based rule weights. Additionally, a methodology is proposed and demonstrated that iteratively improves simulated mission effectiveness. Quantitative analysis is presented on data from 570 simulation runs, which verifies the hypothesis that iterative changes to rule parameters and weights demonstrate significant improvement over baseline performance. For a 36 square mile scenario, results show a 100% increase in finding targets, a 40.2% reduction in time to find a target, a 4.5% increase in area coverage, with a 0% attribution rate due to collisions and near misses

Swarming Reconnaissance Using Unmanned Aerial Vehicles in a Parallel Discrete Event Simulation

Current military affairs indicate that future military warfare requires safer, more accurate, and more fault-tolerant weapons systems. Unmanned Aerial Vehicles (UAV) are one answer to this military requirement. Technology in the UAV arena is moving toward smaller and more capable systems and is becoming available at a fraction of the cost. Exploiting the advances in these miniaturized flying vehicles is the aim of this research. How are the UAVs employed for the future military? The concept of operations for a micro-UAV system is adopted from nature from the appearance of flocking birds, movement of a school of fish, and swarming bees among others. All of these natural phenomena have a common thread: a global action resulting from many small individual actions. This emergent behavior is the aggregate result of many simple interactions occurring within the flock, school, or swarm. In a similar manner, a more robust weapon system uses emergent behavior resulting in no weakest link because the system itself is made up of simple interactions by hundreds or thousands of homogeneous UAVs. The global system in this research is referred to as a swarm. Losing one or a few individual unmanned vehicles would not dramatically impact the swarms ability to complete the mission or cause harm to any human operator. Swarming reconnaissance is the emergent behavior of swarms to perform a reconnaissance operation. An in-depth look at the design of a reconnaissance swarming mission is studied. A taxonomy of passive reconnaissance applications is developed to address feasibility. Evaluation of algorithms for swarm movement, communication, sensor input/analysis, targeting, and network topology result in priorities of each model\u27s desired features. After a thorough selection process of available implementations, a subset of those models are integrated and built upon resulting in a simulation that explores the innovations of swarming UAVs

Design of an UAV swarm

This master thesis tries to give an overview on the general aspects involved in the design of an UAV swarm. UAV swarms are continuoulsy gaining popularity amongst researchers and UAV manufacturers, since they allow greater success rates in task accomplishing with reduced times. Appart from this, multiple UAVs cooperating between them opens a new field of missions that can only be carried in this way. All the topics explained within this master thesis will explain all the agents involved in the design of an UAV swarm, from the communication protocols between them, navigation and trajectory analysis and task allocation

BEHAVIORAL COMPOSITION FOR HETEROGENEOUS SWARMS

Research into swarm robotics has produced a robust library of swarm behaviors that excel at defined tasks such as flocking and area search, many of which have potential for application to a wide range of military problems. However, to be successfully applied to an operational environment, swarms must be flexible enough to achieve a wide array of specific objectives and usable enough to be configured and employed by lay operators. This research explored the use of the Mission-based Architecture for Swarm Composability (MASC) to develop mission-specific tactics as compositions of more general, reusable plays for use with the Advanced Robotic Systems Engineering Laboratory (ARSENL) swarm system. Three tactics were developed to conduct autonomous search of a geographic area and investigation of generated contacts of interest. The tactics were tested in live-flight and virtual environment experiments and compared to a preexisting monolithic behavior implementation completing the same task. Measures of performance were defined and observed that verified the effectiveness of solutions and confirmed the advantages that composition provides with respect to reusability and rapid development of increasingly complex behaviors.Lieutenant Commander, United States NavyApproved for public release. Distribution is unlimited

Toward Computational Modeling of C2 for Teams of Autonomous Systems and People (19th ICCRTS)

19th ICCRTS, Toward Computational Modeling of C2 for Teams of Autonomous Systems and People, Autonomy Track – Paper 116The technological capabilities of autonomous systems (AS) continue to accelerate. Although AS are replacing people in many skilled mission domains and demanding environmental circumstances, people and machines have complementary capabilities, and integrated performance by AS and people working together can be superior to that of either AS or people working alone. We refer to this increasingly important phenomenon as Teams of Autonomous Systems and People (TASP), and we identify a plethora of open, command and control (C2) research, policy and decision making questions. Computational modeling and simulation offer unmatched yet largely unexplored potential to address C2 questions along these lines. The central problem is, this kind of C2 organization modeling and simulation capability has yet to be developed and demonstrated in the TASP domain. This is where our ongoing research project begins to make an important contribution. In this article, we motivate and introduce such TASP research, and we provide an overview of the computational environment used to model and simulate TASP C2 organizations and phenomena. We follow in turn with an approach to characterizing a matrix of diverse TASP C2 contexts, as well as a strategy for specifying, tailoring and using this computational environment to conduct experiments to examine such contexts. We conclude then by summarizing our agenda for continued research along these lines

Ubiquitous supercomputing : design and development of enabling technologies for multi-robot systems rethinking supercomputing

Supercomputing, also known as High Performance Computing (HPC), is almost everywhere (ubiquitous), from the small widget in your phone telling you that today will be a sunny day, up to the next great contribution to the understanding of the origins of the universe.However, there is a field where supercomputing has been only slightly explored - robotics. Other than attempts to optimize complex robotics tasks, the two forces lack an effective alignment and a purposeful long-term contract. With advancements in miniaturization, communications and the appearance of powerful, energy and weight optimized embedded computing boards, a next logical transition corresponds to the creation of clusters of robots, a set of robotic entities that behave similarly as a supercomputer does. Yet, there is key aspect regarding our current understanding of what supercomputing means, or is useful for, that this work aims to redefine. For decades, supercomputing has been solely intended as a computing efficiency mechanism i.e. decreasing the computing time for complex tasks. While such train of thought have led to countless findings, supercomputing is more than that, because in order to provide the capacity of solving most problems quickly, another complete set of features must be provided, a set of features that can also be exploited in contexts such as robotics and that ultimately transform a set of independent entities into a cohesive unit.This thesis aims at rethinking what supercomputing means and to devise strategies to effectively set its inclusion within the robotics realm, contributing therefore to the ubiquity of supercomputing, the first main ideal of this work. With this in mind, a state of the art concerning previous attempts to mix robotics and HPC will be outlined, followed by the proposal of High Performance Robotic Computing (HPRC), a new concept mapping supercomputing to the nuances of multi-robot systems. HPRC can be thought as supercomputing in the edge and while this approach will provide all kind of advantages, in certain applications it might not be enough since interaction with external infrastructures will be required or desired. To facilitate such interaction, this thesis proposes the concept of ubiquitous supercomputing as the union of HPC, HPRC and two more type of entities, computing-less devices (e.g. sensor networks, etc.) and humans.The results of this thesis include the ubiquitous supercomputing ontology and an enabling technology depicted as The ARCHADE. The technology serves as a middleware between a mission and a supercomputing infrastructure and as a framework to facilitate the execution of any type of mission, i.e. precision agriculture, entertainment, inspection and monitoring, etc. Furthermore, the results of the execution of a set of missions are discussed.By integrating supercomputing and robotics, a second ideal is targeted, ubiquitous robotics, i.e. the use of robots in all kind of applications. Correspondingly, a review of existing ubiquitous robotics frameworks is presented and based upon its conclusions, The ARCHADE's design and development have followed the guidelines for current and future solutions. Furthermore, The ARCHADE is based on a rethought supercomputing where performance is not the only feature to be provided by ubiquitous supercomputing systems. However, performance indicators will be discussed, along with those related to other supercomputing features.Supercomputing has been an excellent ally for scientific exploration and not so long ago for commercial activities, leading to all kind of improvements in our lives, in our society and in our future. With the results of this thesis, the joining of two fields, two forces previously disconnected because of their philosophical approaches and their divergent backgrounds, holds enormous potential to open up our imagination for all kind of new applications and for a world where robotics and supercomputing are everywhere.La supercomputación, también conocida como Computación de Alto Rendimiento (HPC por sus siglas en inglés) puede encontrarse en casi cualquier lugar (ubicua), desde el widget en tu teléfono diciéndote que hoy será un día soleado, hasta la siguiente gran contribución al entendimiento de los orígenes del universo. Sin embargo, hay un campo en el que ha sido poco explorada - la robótica. Más allá de intentos de optimizar tareas robóticas complejas, las dos fuerzas carecen de un contrato a largo plazo. Dado los avances en miniaturización, comunicaciones y la aparición de potentes computadores embebidos, optimizados en peso y energía, la siguiente transición corresponde a la creación de un cluster de robots, un conjunto de robots que se comportan de manera similar a un supercomputador. No obstante, hay un aspecto clave, con respecto a la comprensión de la supercomputación, que esta tesis pretende redefinir. Durante décadas, la supercomputación ha sido entendida como un mecanismo de eficiencia computacional, es decir para reducir el tiempo de computación de ciertos problemas extremadamente complejos. Si bien este enfoque ha conducido a innumerables hallazgos, la supercomputación es más que eso, porque para proporcionar la capacidad de resolver todo tipo de problemas rápidamente, se debe proporcionar otro conjunto de características que también pueden ser explotadas en la robótica y que transforman un conjunto de robots en una unidad cohesiva. Esta tesis pretende repensar lo que significa la supercomputación y diseñar estrategias para establecer su inclusión dentro del mundo de la robótica, contribuyendo así a su ubicuidad, el principal ideal de este trabajo. Con esto en mente, se presentará un estado del arte relacionado con intentos anteriores de mezclar robótica y HPC, seguido de la propuesta de Computación Robótica de Alto Rendimiento (HPRC, por sus siglas en inglés), un nuevo concepto, que mapea la supercomputación a los matices específicos de los sistemas multi-robot. HPRC puede pensarse como supercomputación en el borde y si bien este enfoque proporcionará todo tipo de ventajas, ciertas aplicaciones requerirán una interacción con infraestructuras externas. Para facilitar dicha interacción, esta tesis propone el concepto de supercomputación ubicua como la unión de HPC, HPRC y dos tipos más de entidades, dispositivos sin computación embebida y seres humanos. Los resultados de esta tesis incluyen la ontología de la supercomputación ubicua y una tecnología llamada The ARCHADE. La tecnología actúa como middleware entre una misión y una infraestructura de supercomputación y como framework para facilitar la ejecución de cualquier tipo de misión, por ejemplo, agricultura de precisión, inspección y monitoreo, etc. Al integrar la supercomputación y la robótica, se busca un segundo ideal, robótica ubicua, es decir el uso de robots en todo tipo de aplicaciones. Correspondientemente, una revisión de frameworks existentes relacionados serán discutidos. El diseño y desarrollo de The ARCHADE ha seguido las pautas y sugerencias encontradas en dicha revisión. Además, The ARCHADE se basa en una supercomputación repensada donde la eficiencia computacional no es la única característica proporcionada a sistemas basados en la tecnología. Sin embargo, se analizarán indicadores de eficiencia computacional, junto con otros indicadores relacionados con otras características de la supercomputación. La supercomputación ha sido un excelente aliado para la exploración científica, conduciendo a todo tipo de mejoras en nuestras vidas, nuestra sociedad y nuestro futuro. Con los resultados de esta tesis, la unión de dos campos, dos fuerzas previamente desconectadas debido a sus enfoques filosóficos y sus antecedentes divergentes, tiene un enorme potencial para abrir nuestra imaginación hacia todo tipo de aplicaciones nuevas y para un mundo donde la robótica y la supercomputación estén en todos lado