Modelling and Verification of Multiple UAV Mission Using SMV

Model checking has been used to verify the correctness of digital circuits, security protocols, communication protocols, as they can be modelled by means of finite state transition model. However, modelling the behaviour of hybrid systems like UAVs in a Kripke model is challenging. This work is aimed at capturing the behaviour of an UAV performing cooperative search mission into a Kripke model, so as to verify it against the temporal properties expressed in Computation Tree Logic (CTL). SMV model checker is used for the purpose of model checking

Performance analysis of a random search algorithm for distributed autonomous mobile robots

Master'sMASTER OF ENGINEERIN

Teaching a Robot to Drive - A Skill Learning Inspired Approach

Roboter können unser Leben erleichtern, indem sie für uns unangenehme, oder sogar gefährliche Aufgaben übernehmen. Um sie effizient einsetzen zu können, sollten sie autonom, adaptiv und einfach zu instruieren sein. Traditionelle 'white-box'-Ansätze in der Robotik basieren auf dem Verständnis des Ingenieurs der unterliegenden physikalischen Struktur des gegebenen Problems. Ausgehend von diesem Verständnis kann der Ingenieur eine mögliche Lösung finden und es in dem System implementieren. Dieser Ansatz ist sehr mächtig, aber gleichwohl limitiert. Der wichtigste Nachteil ist, dass derart erstellte Systeme von vordefiniertem Wissen abhängen und deswegen jedes neue Verhalten den gleichen, teuren Entwicklungszyklus benötigt. Im Gegensatz dazu sind Menschen und einige andere Tiere nicht auf ihre angeborene Verhalten beschränkt, sondern können während ihrer Lebenszeit vielzählige weitere Fähigkeiten erwerben. Zusätzlich scheinen sie dazu kein detailliertes Wissen über den (physikalische) Ablauf einer gegebenen Aufgabe zu benötigen. Diese Eigenschaften sind auch für künstliche Systeme wünschenswert. Deswegen untersuchen wir in dieser Dissertation die Hypothese, dass Prinzipien des menschlichen Fähigkeitslernens zu alternativen Methoden für adaptive Systemkontrolle führen können. Wir untersuchen diese Hypothese anhand der Aufgabe des Autonomen Fahrens, welche ein klassiches Problem der Systemkontrolle darstellt und die Möglichkeit für vielfältige Applikationen bietet. Die genaue Aufgabe ist das Erlernen eines grundlegenden, antizipatorischen Fahrverhaltens von einem menschlichem Lehrer. Nachdem wir relevante Aspekte bezüglich des menschlichen Fähigkeitslernen aufgezeigt haben, und die Begriffe 'interne Modelle' und 'chunking' eingeführt haben, beschreiben wir die Anwendung dieser auf die gegebene Aufgabe. Wir realisieren chunking mit Hilfe einer Datenbank in welcher Beispiele menschlichen Fahreverhaltens gespeichert werden und mit Beschreibungen der visuell erfassten Strassentrajektorie verknüpft werden. Dies wird zunächst innerhalb einer Laborumgebung mit Hilfe eines Roboters verwirklicht und später, im Laufe des Europäischen DRIVSCO Projektes, auf ein echtes Auto übertragen. Wir untersuchen ausserdem das Erlernen visueller 'Vorwärtsmodelle', welche zu den internen Modellen gehören, sowie ihren Effekt auf die Kontrollperformanz beim Roboter. Das Hauptresultat dieser interdisziplinären und anwendungsorientierten Arbeit ist ein System, welches in der Lage ist als Antwort auf die visuell wahrgenommene Strassentrajektorie entsprechende Aktionspläne zu generieren, ohne das dazu metrische Informationen benötigt werden. Die vorhergesagten Aktionen in der Laborumgebung sind Lenken und Geschwindigkeit. Für das echte Auto Lenken und Beschleunigung, wobei die prediktive Kapazität des Systems für Letzteres beschränkt ist. D.h. der Roboter lernt autonomes Fahren von einem menschlichen Lehrer und das Auto lernt die Vorhersage menschlichen Fahrverhaltens. Letzteres wurde während der Begutachtung des Projektes duch ein internationales Expertenteam erfolgreich demonstriert. Das Ergebnis dieser Arbeit ist relevant für Anwendungen in der Roboterkontrolle und dabei besonders in dem Bereich intelligenter Fahrerassistenzsysteme

Design of a walking robot

Carnegie Mellon University's Autonomous Planetary Exploration Program (APEX) is currently building the Daedalus robot; a system capable of performing extended autonomous planetary exploration missions. Extended autonomy is an important capability because the continued exploration of the Moon, Mars and other solid bodies within the solar system will probably be carried out by autonomous robotic systems. There are a number of reasons for this - the most important of which are the high cost of placing a man in space, the high risk associated with human exploration and communication delays that make teleoperation infeasible. The Daedalus robot represents an evolutionary approach to robot mechanism design and software system architecture. Daedalus incorporates key features from a number of predecessor systems. Using previously proven technologies, the Apex project endeavors to encompass all of the capabilities necessary for robust planetary exploration. The Ambler, a six-legged walking machine was developed by CMU for demonstration of technologies required for planetary exploration. In its five years of life, the Ambler project brought major breakthroughs in various areas of robotic technology. Significant progress was made in: mechanism and control, by introducing a novel gait pattern (circulating gait) and use of orthogonal legs; perception, by developing sophisticated algorithms for map building; and planning, by developing and implementing the Task Control Architecture to coordinate tasks and control complex system functions. The APEX project is the successor of the Ambler project

Modèle multi-agents d'aide à la décision pour la gestion des services préhospitaliers d'urgence

La nécessité de mieux comprendre et maîtriser la complexité des systèmes d’information exige le développement de nouvelles méthodes de modélisation et de résolution de problèmes. Ce travail de recherche s’intéresse à la conception et la modélisation d’un système d’aide à la décision dans lequel le savoir et les compétences de l’expert permettent d’analyser et de proposer de nouveaux modèles multi-agents. Le développement d’un tel modèle relève un certain nombre de difficultés de conception, liés notamment à l’efficience et l’efficacité du processus de calcul et de résolution du problème, auxquels on apporte des éléments de solution. Beaucoup de systèmes complexes se caractérisent par des dynamiques non linéaires, désordonnées et aléatoires, en résumé compliquées dans le sens où leur assimilation demande du temps et du talent. Les méthodes mathématiques classiques (équations différentielles, modèles probabilistes, etc.) peuvent s’avérer inappropriées pour modéliser de tels systèmes dans lesquels l’interaction occupe un rôle très important. La modélisation à base d’agents réactifs est l’une des techniques de modélisation microscopique les plus répandues. Pourquoi choisir une modélisation orientée agent plutôt qu’un autre méta-modèle de modélisation? Premièrement, le modèle agent est très riche. Il aide ainsi le concepteur à schématiser facilement des processus qualitatifs et quantitatifs et permet d’interagir des entités hétérogènes aux architectures diverses. Pourtant, la raison principale est souvent liée à la vocation de modélisation : bien appréhender la relation entre actions/comportements individuels et action/comportement collectif. Ce travail est mené principalement dans un cadre applicatif lié au problème de planification et de gestion des services préhospitaliers d’urgence (SPU). En effet, on trouve un ensemble de recherches qui traitent le sujet de la gestion et de la planification des SPU. Chaque travail de recherche traite une problématique bien spécifique de ce domaine, soit la confection des horaires des ambulanciers, soit la gestion de la demande en services préhospitaliers, ou la gestion des véhicules/ambulances, etc. Cette thèse s’intéresse à la problématique de planification des services préhospitaliers d’urgence afin de mieux répondre à la demande de service et par conséquence diminuer le temps-réponse des ambulanciers. Elle adopte une approche de résolution globale et intégrée. Elle vise la proposition d’un modèle sous forme de différentes composantes d’aide à la décision. Elle intègre des techniques d’optimisation touchant à la fois la planification des horaires, la gestion des remplacements, la gestion de la flotte de véhicules, la gestion de la capacité des dépôts, la couverture de la demande et la gestion des événements spéciaux. Le modèle proposé est basé sur une architecture multi-agents et permet de répondre aux contraintes et aux aléas survenus lors de la planification des SPU. Le travail réalisé dans le cadre de cette thèse est articulé autour de trois articles suivants : • « Integrated and global approach (IGAP) based on multi-agent systems for the management of prehospital emergency services », soumis à Computers & Industrial Engineering de Elsevier. Cet article présente une introduction aux systèmes multiagents appliqués aux SPU et propose une nouvelle approche globale et intégrée pour sa résolution appelée IGAP. • « Scheduling Model for Prehospital Emergency Services », soumis à l’European Journal of Operational Research de Elsevier. Cet article traite le problème de confection d’horaires des techniciens ambulanciers. Notre contribution réside dans la proposition d’un modèle mathématique appelé « set covering » qui résout un problème de couverture intégré dans un nouveau système suffisamment flexible de confection d’horaires. • « Multi-Agent Decision-Making Support Model for the Management of Prehospital Emergency Services », publié dans International Journal of Machine Learning and Computing, de IACSIT. Cet article porte sur le thème de la modélisation et de l’aide à la décision dans le cadre des systèmes complexes dont on propose une architecture à base d’agents d’aide à la décision dédiée à la gestion des services préhospitaliers d’urgence

Coordination schemes for distributed boundary coverage with a swarm of miniature robots:synthesis, analysis and experimental validation

We provide a comparison of a series of original coordination mechanisms for the distributed boundary coverage problem with a swarm of miniature robots. Our analysis is based on real robot experimentation and models at different levels of abstraction. Distributed boundary coverage is an instance of the distributed coverage problem and has applications such as inspection of structures, de-mining, cleaning, and painting. Coverage is a particularly good example for the benefits of a multi-robot approach due to the potential for parallel task execution and additional robustness out of redundancy. The constraints imposed by a potential application, the autonomous inspection of a jet turbine engine, were our motivation for the algorithms considered in this thesis. Thus, there is particular emphasis on how algorithms perform under the influence of sensor and actuator noise, limited computational and communication capabilities, as well as on the policies about how to cope with such problems. The algorithms developed in this dissertation can be classified into reactive and deliberative algorithms, as well as non-collaborative and collaborative algorithms. The performance of these algorithms ranges from very low to very high, corresponding to highly redundant coverage to near-optimal partitioning of the environments, respectively. At the same time, requirements and assumptions on the robotic platform and the environment (from no communication to global communication, and from no localization to global localization) are incrementally raised. All the algorithms are robust to sensor and actuator noise and gracefully decay to the performance of a randomized algorithm as a function of an increased noise level and/or additional hardware constraints. Although the deliberative algorithms are fully deterministic, the actual performance is probabilistic due to inevitable sensor and actuator noise. For this reason, probabilistic models are used for predicting time to complete coverage and take into account sensor and actuator noise calibrated by using real hardware. For reactive systems with limited memory, the performance is captured using a compact representation based on rate equations that track the expected number of robots in a certain state. As the number of states explode for the deliberative algorithms that require a substantial use of memory, this approach becomes less tractable with the amount of deliberation performed, and we use Discrete Event System (DES) simulation in these cases. Our contribution to the domain of multi-robot systems is three-fold. First, we provide a methodology for system identification and optimal control of a robot swarm using probabilistic models. Second, we develop a series of algorithms for distributed coverage by a team of miniature robots that gracefully decay from a near-optimal performance to the performance of a randomized approach under the influence of sensor and actuator noise. Third, we design an implement a miniature inspection platform based on the miniature robot Alice with ZigBee ready communication capabilities and color vision on a foot-print smaller than 2 × 2 × 3 cm3

Task-Oriented Exploration: A Multi-Criteria Decision Making Approach for Robotic Exploration

In robotic planetary exploration missions, robots are deployed to autonomously explore and map the large and unstructured environments of planetary surfaces. While a robot should be able to execute a mission task mainly autonomously, for space exploration missions, it is important to have the opportunity to observe and adapt the robotic exploration task. Operators and scientists require to supervise the robot at the available communication time slots and understand the decisions made by the robot. For this we propose a generalized concept for robotic exploration based on Multi-Criteria Decision Making (MCDM) to model, implement and conduct exploration tasks. Our general formulation supports scientists by designing the autonomous exploration behavior of a robot to reach specific missions goals. In robotic exploration tasks, robots repeatedly decide where to move next. We define locations at the boundary to unknown areas - exploration goals - and locations in already visited areas - revisiting goals - to be the solution space of this decision problem. To model a certain exploration behavior, the goal locations are evaluated by a set of criteria and conditions. The criteria and condition values for each goal location are compared, applying a MCDM method to find the next goal location, which best matches the defined mission goal. Thereby, we introduce two novel multi-attribute utility functions and transfer the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE II) to solve decision making in robotic exploration. To cope with the limited computational resources of space rovers, we extend the PROMETHEE II algorithm to decrease the required computational resources. Applying our generalized concept, we examine four exploration use cases, deduced from the Exploration Roadmap of the International Space Exploration Coordination Group (ISECG). In the first use case, the robot has to autonomously survey a region of interest. To tackle the trade-off between exploration efficiency and map quality, we implement an integrated exploration, which applies active loop closing to optimize an underlying SLAM graph. In our second use case, we implement a directed exploration to increase the scientific output while exploring a region of interest. It incorporates knowledge about the probability of detecting a feature of interest, i.e., a specific type of rock requested by the scientists. As our third use case, we implement an exploration behavior in the fashion of drive-by science, whereby the robot is directed to a predefined point of interest, while simultaneously gathering new information about the environment on its way. For our fourth use case, we apply the same concept to model a multi-robot exploration task, which coordinates a heterogeneous team of two robots. We demonstrate all four use cases on real or simulated space rover prototype hardware. In a total of more than sixty experiments, we evaluate our methods and analyze the implemented exploration behavior

SYNERGY OF BUILDING CYBERSECURITY SYSTEMS

The development of the modern world community is closely related to advances in computing resources and cyberspace. The formation and expansion of the range of services is based on the achievements of mankind in the field of high technologies. However, the rapid growth of computing resources, the emergence of a full-scale quantum computer tightens the requirements for security systems not only for information and communication systems, but also for cyber-physical systems and technologies. The methodological foundations of building security systems for critical infrastructure facilities based on modeling the processes of behavior of antagonistic agents in security systems are discussed in the first chapter. The concept of information security in social networks, based on mathematical models of data protection, taking into account the influence of specific parameters of the social network, the effects on the network are proposed in second chapter. The nonlinear relationships of the parameters of the defense system, attacks, social networks, as well as the influence of individual characteristics of users and the nature of the relationships between them, takes into account. In the third section, practical aspects of the methodology for constructing post-quantum algorithms for asymmetric McEliece and Niederreiter cryptosystems on algebraic codes (elliptic and modified elliptic codes), their mathematical models and practical algorithms are considered. Hybrid crypto-code constructions of McEliece and Niederreiter on defective codes are proposed. They can significantly reduce the energy costs for implementation, while ensuring the required level of cryptographic strength of the system as a whole. The concept of security of corporate information and educational systems based on the construction of an adaptive information security system is proposed. ISBN 978-617-7319-31-2 (on-line)ISBN 978-617-7319-32-9 (print) ------------------------------------------------------------------------------------------------------------------ How to Cite: Yevseiev, S., Ponomarenko, V., Laptiev, O., Milov, O., Korol, O., Milevskyi, S. et. al.; Yevseiev, S., Ponomarenko, V., Laptiev, O., Milov, O. (Eds.) (2021). Synergy of building cybersecurity systems. Kharkiv: РС ТЕСHNOLOGY СЕNTЕR, 188. doi: http://doi.org/10.15587/978-617-7319-31-2 ------------------------------------------------------------------------------------------------------------------ Indexing:                    Розвиток сучасної світової спільноти тісно пов’язаний з досягненнями в області обчислювальних ресурсів і кіберпростору. Формування та розширення асортименту послуг базується на досягненнях людства у галузі високих технологій. Однак стрімке зростання обчислювальних ресурсів, поява повномасштабного квантового комп’ютера посилює вимоги до систем безпеки не тільки інформаційно-комунікаційних, але і до кіберфізичних систем і технологій. У першому розділі обговорюються методологічні основи побудови систем безпеки для об'єктів критичної інфраструктури на основі моделювання процесів поведінки антагоністичних агентів у систем безпеки. У другому розділі пропонується концепція інформаційної безпеки в соціальних мережах, яка заснована на математичних моделях захисту даних, з урахуванням впливу конкретних параметрів соціальної мережі та наслідків для неї. Враховуються нелінійні взаємозв'язки параметрів системи захисту, атак, соціальних мереж, а також вплив індивідуальних характеристик користувачів і характеру взаємовідносин між ними. У третьому розділі розглядаються практичні аспекти методології побудови постквантових алгоритмів для асиметричних криптосистем Мак-Еліса та Нідеррейтера на алгебраїчних кодах (еліптичних та модифікованих еліптичних кодах), їх математичні моделі та практичні алгоритми. Запропоновано гібридні конструкції криптокоду Мак-Еліса та Нідеррейтера на дефектних кодах. Вони дозволяють істотно знизити енергетичні витрати на реалізацію, забезпечуючи при цьому необхідний рівень криптографічної стійкості системи в цілому. Запропоновано концепцію безпеки корпоративних інформаційних та освітніх систем, які засновані на побудові адаптивної системи захисту інформації. ISBN 978-617-7319-31-2 (on-line)ISBN 978-617-7319-32-9 (print) ------------------------------------------------------------------------------------------------------------------ Як цитувати: Yevseiev, S., Ponomarenko, V., Laptiev, O., Milov, O., Korol, O., Milevskyi, S. et. al.; Yevseiev, S., Ponomarenko, V., Laptiev, O., Milov, O. (Eds.) (2021). Synergy of building cybersecurity systems. Kharkiv: РС ТЕСHNOLOGY СЕNTЕR, 188. doi: http://doi.org/10.15587/978-617-7319-31-2 ------------------------------------------------------------------------------------------------------------------ Індексація:                 &nbsp

Third International Symposium on Space Mission Operations and Ground Data Systems, part 1

Under the theme of 'Opportunities in Ground Data Systems for High Efficiency Operations of Space Missions,' the SpaceOps '94 symposium included presentations of more than 150 technical papers spanning five topic areas: Mission Management, Operations, Data Management, System Development, and Systems Engineering. The papers focus on improvements in the efficiency, effectiveness, productivity, and quality of data acquisition, ground systems, and mission operations. New technology, techniques, methods, and human systems are discussed. Accomplishments are also reported in the application of information systems to improve data retrieval, reporting, and archiving; the management of human factors; the use of telescience and teleoperations; and the design and implementation of logistics support for mission operations