Cooperative Acoustic Navigation Scheme for Heterogenous Autonomous Underwater Vehicles

International audienceCooperative Acoustic Navigation Scheme for Heterogenous Autonomous Underwater Vehicle

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties

A cooperative advanced driver assistance and safety system for connected and automated vehicles

Konfliktsituationen mit mehreren Beteiligten sind für Fahrzeugführer und konventionelle Fahrerassistenz- und Sicherheitssysteme durch ihre hohe Komplexität schwer beherrschbar. So geschehen viele Unfälle auf den Straßen dieser Welt, die durch gemeinschaftlich abgestimmte Fahrmanöver verhindert oder in ihren Unfallfolgen gemindert werden könnten. Die vorliegende Arbeit adressiert dieses Potenzial und beschäftigt sich mit der Entwicklung und prototypischen Umsetzung eines fahrzeugübergreifenden kooperativen Fahrerassistenz- und Sicherheitssystems, welches mehrere Fahrzeuge über eine funkbasierte Kommunikation miteinander verbindet, sowie unfallfreie Lösungen berechnet und durchführt. In diesem Zusammenhang werden drei Forschungsfragen aufgestellt, die eine Definition von kooperativem Verhalten, eine Methode zur Koordination der anfallenden Aufgaben (Aufgabenkoordination) und eine Methode zur gemeinsamen Fahrmanöverplanung (Fahrmanöverkoordination) adressieren. Der Stand der Wissenschaft und Technik bezüglich der Forschungsfragen wird mithilfe einer systematischen Literaturstudie ermittelt, die für den Leser in einem Überblick dargestellt und hinsichtlich einer möglichen Beantwortung der Forschungsfragen ausgewertet wird. Es zeigt sich, dass die drei Forschungsfragen mit ihren Anforderungen bislang unbeantwortet sind. Zur Definition von kooperativem Verhalten werden Eigenschaften von diesem aufgezeigt, die in notwendige und hinreichende Bedingungen überführt werden. Mit der zusätzlichen Berücksichtigung von Reziprozität ergibt sich eine Definition von kooperativem Verhalten, welche durch die Steigerung des Gesamtnutzens die Unterscheidung zwischen unkooperativem Verhalten auf der einen Seite und rational-kooperativem, altruistisch-kooperativem bzw. egoistisch-kooperativem Verhalten auf der anderen Seite ermöglicht. Ein Vergleich mit den aus dem Stand der Technik bekannten Definitionen zeigt den Neuigkeitswert der entwickelten Definition. In ausgewählten Situationen wird die Definition in Simulationen angewandt.Critical situations involving multiple vehicles are rarely controlled by the associated drivers. This is one reason for the remaining number of accidents which could possibly be prevented or at least mitigated with jointly planned and conducted driving maneuvers. This potential is addressed in the dissertation at hand by developing a prototypical cooperative driver assistance and safety system coordinating multiple vehicles cooperatively using vehicle-to-vehicle-communication. In this context, three research questions reflect challenges on the road towards such a system. The research questions deal with defining a cooperative behavior, creating a method allowing to allocate coordinative tasks (task coordination), and generating a method enabling to plan joint cooperative maneuvers (maneuver coordination). Regarding the proposed research questions, a systematic literature review reveals the state-of-the-art which is first presented in an overview and afterwards used to derive open issues. The result is that the three research questions remain relevant and unanswered. In order to define cooperative behavior, properties are identified and categorized in sufficient and necessary conditions. An additional consideration of reciprocity enables the derivation of a definition of cooperative behavior which aims to increase the total utility. Cooperative behavior may further be separated into rational-cooperative, altruistic-cooperative, and egoistic-cooperative behavior. A comparison with known definitions of the state-of-the-art demonstrates the innovation of the novel definition, which is applied in chosen situations

Controle de missão baseado na teoria de controle supervisório com aplicação a veículos subaquáticos autônomos

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Automação e Sistemas, Florianópolis, 2015.Veículo subaquático autônomo (AUV, do inglês autonomous underwater vehicle) é uma classe de dispositivo robótico que se move sob a água, controlado pelo seu próprio sistema embarcado, acionado por um sistema de propulsão adequado e com fonte autônoma de energia. O Sistema de Controle de Missão (SCM) é o elemento do sistema embarcado de um veículo autônomo responsável em coordenar as ações realizadas pelos demais subsistemas, guiando o veículo durante todas as fases da missão, com base em um plano previamente elaborado e no comportamento discreto dos diversos componentes do veículo. Esta tese propõe uma arquitetura para o SCM baseado em dois componentes principais: uma estrutura de controle supervisório e um gerenciador de missão. O primeiro componente é baseado na Teoria de Controle Supervisório (TCS). A TCS é neste caso usada para a modelagem dos vários subsistemas e restrições relacionadas com a realização de missões de AUVs em ambientes não-estruturados, e para a síntese de supervisores responsáveis em garantir que especificações de segurança e operação sejam atendidas para qualquer missão do veículo. O segundo componente é responsável pela execução de um plano de missão, escolhendo a melhor sequência de eventos habilitada pelo controle supervisório segundo um critério de otimização baseado em algoritmos de planejamento e busca. Para validação da arquitetura proposta, o SCM é implementado empregando o ROS (robot operating system) com a estrutura de controle supervisório integrada mediante geração automática de código. O teste do SCM proposto é realizado em um ambiente para simulação do comportamento dinâmico contínuo e dirigido a eventos de todo o sistema embarcado de um AUV. Os resultados demonstram que o SCM proposto é capaz de garantir a realização de missões em ambientes não-estruturados, atendendo a critérios de segurança especificados pelos modelos formais da TCS. Ao mesmo tempo, o SCM permite o replanejamento de missões ao gerar um plano de missão alternativo possibilitando o tratamento de diversas situações não previstas no plano original. Além disso, a arquitetura proposta para o SCM combina ações deliberativas, que envolvem planejamento, com ações reativas sem necessidade de planejamento e com tempos de execuções relativamente pequenos.Abstract : Autonomous underwater vehicle (AUV) is a class of robotic device that moves beneath the water, it is controlled by its own embedded system, triggered by a suitable propulsion system and with an autonomous source of energy. The Mission Control System (MCS) is the element of the embedded system of an autonomous vehicle responsible for coordinating the actions conducted by several subsystems, driving the vehicle during all phases of the mission based on a previously elaborated plan and on the discrete behavior of the vehicle remaining components. This thesis proposes an MCS architecture based on two main components: a supervisory control structure and a mission manager. The supervisory structure is based on Supervisory Control Theory (SCT) and it is used for modelling the several subsystems and constraints related to the AUV missions in unstructured environments, as well as for the synthesis of supervisores responsible for ensuring that safety and operation specifications are met for any kind of vehicle mission. The second component, the mission manager, is responsabile for carrying out a mission plan, choosing the best sequence of events enabled by the supervisory control according to an optimization criterion based on planning and search algorithms. To validate the proposed architecture, the MCS is implemented using ROS (robot operating system) with the supervisory control models integrated through automatic code generation. The test of the MCS is performed in a simulation environment that emulates the whole AUV continous and event-driven dynamics. The results demonstrate that the proposed MCS is capable of performing missions in unstructured environments, meeting safety criteria specified by the formal models of the CST. In the meantime, the MCS allows the mission replanning by generating an alternative mission enabling the treatment of several situtations unforeseen in the original plan. Moreover, the proposed architecture for the MCS combines deliberative actions, related to planning, with reactive actions without planning and with relatively small execution times