Generic Architecture for Multi-AUV Cooperation Based on a Multi-Agent Reactive Organizational Approach

International audienceBecause Autonomous Underwater Vehicles (AUVs) have limited perception and communication capabilities, designing efficient AUV flotillas is challenging. Existing solutions are often strongly related to (1) a specific kind of mission and (2) the nature of the considered AUVs. So, it is difficult to reuse these approaches when switching to another mission context. This paper proposes a generic multi-agent based layered architecture for designing and specifying AUV flotillas at a high level of abstraction, regardless of the AUVs characteristics and skills. To this end, an organizational model is used to ease and regulate interactions between heterogeneous AUVs and combined with a behavioral reactive approach for limiting communication

Service-oriented agent architecture for autonomous maritime vehicles

Advanced ocean systems are increasing their capabilities and the degree of autonomy more and more in order to perform more sophisticated maritime missions. Remotely operated vehicles are no longer cost-effective since they are limited by economic support costs, and the presence and skills of the human operator. Alternatively, autonomous surface and underwater vehicles have the potential to operate with greatly reduced overhead costs and level of operator intervention. This Thesis proposes an Intelligent Control Architecture (ICA) to enable multiple collaborating marine vehicles to autonomously carry out underwater intervention missions. The ICA is generic in nature but aimed at a case study where a marine surface craft and an underwater vehicle are required to work cooperatively. They are capable of cooperating autonomously towards the execution of complex activities since they have different but complementary capabilities. The architectural foundation to achieve the ICA lays on the flexibility of service-oriented computing and agent technology. An ontological database captures the operator skills, platform capabilities and, changes in the environment. The information captured, stored as knowledge, enables reasoning agents to plan missions based on the current situation. The ICA implementation is verified in simulation, and validated in trials by means of a team of autonomous marine robots. This Thesis also presents architectural details and evaluation scenarios of the ICA, results of simulations and trials from different maritime operations, and future research directions

Approches environnement-centrées pour la simulation de systèmes multi-agents: Pour un déplacement de la complexité des agents vers l'environnement

This habilitation thesis synthesizes research works which are mainly related to the field of Multi-Agent Based Simulation (MABS). MABS is a general framework for modeling and experimenting with systems in which the dynamics emerges from local interactions among individuals (autonomous agents). Examples of use range from the study of natural systems (e.g. ant colonies, crowds or traffic jams) to the engineering of artificial ones (e.g., collective robotics, distributed artificial intelligence-based softwares). To this end, MABS modeling represents the behavior of individuals, their environment and interactions, so that global dynamics can be computed and studied from the bottom up. In this context, we have been investigating research on the theory and practice of MABS from two different perspectives : (1) the design of generic abstractions dedicated to the modeling of multi-agent dynamics (e.g., the IRM4S model) and (2) the engineering of MABS (MaDKit and TurtleKit platforms). Besides, we have been experimenting with MABS in different application domains such as image processing, video games, and collective robotics. Contrary to approaches that put the emphasis on the agent behaviors, all these works have been done by considering the environment of the agents as a first order abstraction. In this thesis, we first reflect upon the research we have conducted according to this perspective. Next, we show how we actually use this perspective to propose an original approach for using General-Purpose processing on Graphics Processing Units (GPGPU) within MABS, and then present the research perspectives related to our positioning.Les travaux de recherche synthétisés dans ce mémoire s’inscrivent principalement dans le domaine de la modélisation et de la simulation de systèmes multi-agents (SMA). La simulation multi-agents met en œuvre des modèles où les individus, leur environnement et leurs interactions sont directement représentés. Dans ces modèles, chaque individu –agent autonome– possède son propre comportement et produit ses actions en fonction d’une perception locale de son environnement. Ainsi, la simulation multi-agents est utilisée pour étudier des systèmes naturels comme les colonies de fourmis, les dynamiques de foules ou le trafic urbain, mais aussi pour concevoir des systèmes artificiels, par exemple dans le cadre de la robotique collective ou le développement de logiciels basés sur de l’intelligence artificielle distribuée. Dans ce cadre, nos recherches ont porté sur des problématiques liées à la modélisation de simulations multi-agents, avec la proposition de modèles formels et conceptuels (e.g. le modèle IRM4S) et d’outils logiciels génériques (plates-formes MaDKit et TurtleKit), et sur leur utilisation dans divers domaines tels que le jeu vidéo, le traitement numérique de l’image ou la robotique collective. Contrairement aux approches centrées sur la conception des comportements individuels, dans ces travaux l’environnement des agents est considéré comme une abstraction de premier ordre. Dans ce mémoire, nous dressons tout d’abord un bilan de nos recherches en argumentant l’intérêt d’une telle démarche pour les modèles multi-agents. Nous montrons ensuite comment celle-ci nous a récemment permis de proposer une approche originale dans le cadre de l’utilisation du calcul haute performance sur carte graphique (GPGPU) pour la simulation de SMA, avant de présenter les perspectives de recherche associées à notre positionnement

Navigational Strategies for Control of Underwater Robot using AI based Algorithms

Autonomous underwater robots have become indispensable marine tools to perform various tedious and risky oceanic tasks of military, scientific, civil as well as commercial purposes. To execute hazardous naval tasks successfully, underwater robot needs an intelligent controller to manoeuver from one point to another within unknown or partially known three-dimensional environment. This dissertation has proposed and implemented various AI based control strategies for underwater robot navigation. Adaptive versions of neuro-fuzzy network and several stochastic evolutionary algorithms have been employed here to avoid obstacles or to escape from dead end situations while tracing near optimal path from initial point to destination of an impulsive underwater scenario. A proper balance between path optimization and collision avoidance has been considered as major aspects for evaluating performances of proposed navigational strategies of underwater robot. Online sensory information about position and orientation of both target and nearest obstacles with respect to the robot’s current position have been considered as inputs for path planners. To validate the feasibility of proposed control algorithms, numerous simulations have been executed within MATLAB based simulation environment where obstacles of different shapes and sizes are distributed in a chaotic manner. Simulation results have been verified by performing real time experiments of robot in underwater environment. Comparisons with other available underwater navigation approaches have also been accomplished for authentication purpose. Extensive simulation and experimental studies have ensured the obstacle avoidance and path optimization abilities of proposed AI based navigational strategies during motion of underwater robot. Moreover, a comparative study has been performed on navigational performances of proposed path planning approaches regarding path length and travel time to find out most efficient technique for navigation within an impulsive underwater environment

Comunidades Inteligentes para la Construcción y Gestión de Arquitecturas Optimizadas de de Sistemas Multiagente

[ES] El desarrollo de sistemas informáticos es una labor más o menos costosa en función de su complejidad. El hecho de poder reutilizar, parcial o totalmente, trozos de un sistema para otros desarrollos, implica una reducción en el tiempo empleado, una mayor facilidad de implementación y evita la redundancia de funcionalidades. Este planteamiento llevado a los sistemas multiagente ha de tener en cuenta las características propias de los agentes, para lo cual se requiere que la reutilización pueda llevarse a cabo a partir de pequeños subsistemas de agentes especializados con una organización establecida. Además, para explotar la capacidad de estos pequeños subsistemas de agentes es necesaria una arquitectura que tenga como finalidad la coordinación de los mismos, y que de forma modular y escalada, pueda desarrollarse para lograr objetivos de mayor complejidad. A lo largo de este trabajo se llevará a cabo un estudio de las características de los agentes y sistemas multiagente, asi como de las organizaciones humanas y su implementación a partir de las organizaciones virtuales, destacando su importancia y efectividad en el desarrollo actual de sistemas multiagente. Llegado este punto se realizará el diseño de SCODA (Distributed and Specialized Agent COmmunities), una nueva arquitectura modular para el desarrollo de sistemas multiagente. Mediante SCODA se permite el desarrollo de sistemas multiagente bajo una filosofía modular especializada, a través de la cual las funcionalidades del sistema puedan ir ampliándose, de forma escalada, en función de las necesidades. SCODA se compone de pequeños subsistemas de agentes, denominados Comunidades Inteligentes Especializadas (CIE), los cuales proveen las funcionalidades necesarias para resolver las necesidades requeridas a través de servicios distribuidos. Mediante estas CIE se permite una escalabilidad de los sistemas de forma que puedan ser reutilizadas en diferentes desarrollos, independientemente de su finalidad. La validación de esta arquitectura se realizará a partir de un caso de estudio centrado en tareas principalmente logísticas, debido a la variedad de situaciones que pueden darse en este tipo de ambientes. A partir de este caso de estudio se analizará y evaluará el comportamiento de la arquitectura y podrá llevarse a cabo su validaciónComputers systems development is more or less difficult task according to its complexity. The fact of being able to re-use, partially or completely, pieces of a system for other developments, involves a time reduction, a major implementation facility and avoids the functionalities redundancy. This aim applied to multiagent systems has to bear in mind the own characteristics of the agents, for which it is needed that the re-using could be carried out from small subsystems of specialized agents with an established organization. Also, to improve the capacity of these small subsystems of agents, is necessary an architecture, that has the objective to take the coordination of the same ones, and in a modular and scalable way, could develop to achieve aims with a major complexity. Throughout this work will be carried out a study of the characteristics of the agents and multiagent systems, as well as of human organizations and its deployment on virtual organizations, highlighting its importance and effectiveness in the current development of multiagent systems. From here it will be developed the design of SCODA (Distributed and Specialized Agent Communities), a new modular architecture for the development of multiagent systems. By means of SCODA, is allowed that multiagent systems could be developed from a specialized modular philosophy, across it the functionalities of the system can be extended in scaled form according to the objectives. SCODA is composed by small subsystems of agents named, Specialized Intelligent Communities (SCI), which provide the necessary functionalities to solve the objectives needed across distributed services. By means of these CIE, scalability of the systems is allowed, so that they could be re-used in different developments, independently of his purpose. SCODA is integrated by smaller subsystems of agents, called Intelligent Communities Specialized (SCI), which provide the functionality necessary to resolve the aims, using distributed services. These SCI allow a scalability of the systems so that can be reused in different developments, regardless of its purpose. The validation of this architecture will be realized through a case of study, focused on logistical tasks mainly due to the variety of situations that may arise in this kind of environments. From this case of study, we will analyze and assess the behaviour of the architecture and will carry out its validation