A cooperative architecture for target localization using underwater vehicles

Nous nous intéressons à l'architecture de robots marins et sous-marins autonomes dans le cadre de missions nécessitant leur coopération. Cette coopération s'avère difficile du fait que la communication (acoustique) est très contrainte en termes de débit et de portée.  Notre travail se place dans le contexte de missions d'exploration pour détecter des éléments particuliers sur les fonds marins, et en particulier des sources d'eau chaude. Pour cela, le véhicule sous-marin parcours des segments de droite pré-planifiés et rejoint des points de rendez-vous (points de communication). Ces derniers permettent d'assurer le suivi de bon déroulement de la mission, mais surtout de mettre en oeuvre des schémas de coopération entre les véhicules sous-marins. Au fur et à mesure de l'exploration, les sous-marins construisent et mettent à jour une représentation de l'environnement qui décrit les probabilités de localisation de sources. Une approche adaptative exploite ces informations et permet de dévier les sous-marins de leurs plan initial pour augmenter la quantité d'information, tout en respectant les contraintes du plan initial, et en particulier les rendez-vous de communication. Lors des rendez-vous, chaque véhicule échange ses données avec les autres, en ne transmettant que les informations nécessaires à la mise en place de schémas de coopération. L'ensemble de ces fonctions sont intégrées au sein de l'architecture existante T-REX, pour laquelle nous proposons des composants supplémentaires qui permettent la cartographie des fonds et la définition de schémas de coopération. Différentes simulations permettent d'évaluer les travaux proposés. ABSTRACT : There is a growing research interest in Autonomous Underwater Vehicles (AUV), due to the need for increasing our knowledge about the deep sea and understanding the effects the human way of life has on it. This need has pushed the development of new technologies to design more efficient and more autonomous underwater vehicles. Autonomy refers, in the context of this thesis, to the “decisional autonomy”, i.e. the capability of taking decisions, in uncertain, varying and unknown environments. A more recent concern in AUV area is to consider a fleet of vehicles (AUV, ASV, etc). Indeed, multiple vehicles with heterogeneous capabilities have several advantages over a single vehicle system, and in particular the potential to accomplish tasks faster and better than a single vehicle. Underwater target localization using several AUVs (Autonomous Underwater Vehicles) is a challenging issue. A systematic and exhaustive coverage strategy is not efficient in term of exploration time: it can be improved by making the AUVs share their information and cooperate to optimize their motions. The contribution of this thesis is the definition of an architecture that integrates such a strategy that adapts each vehicle motions according to its and others’ sensory information. Communication points are required to make underwater vehicles exchange information : for that purpose the system involves one ASV (Autonomous Surface Vehicle), that helps the AUVs re-localize and exchange data, and two AUVs that adapt their strategy according to gathered information, while satisfying the associated communication constraints. Each AUV is endowed with a sensor that estimates its distance with respect to targets, and cooperates with others to explore an area with the help of an ASV. To provide the required autonomy to these vehicles, we build upon an existing system (T-REX) with additional components, which provides an embedded planning and execution control framework. Simulation results are carried out to evaluate the proposed architecture and adaptive exploration strategy

Dynamic Interest Points: A Formalism to Identify Areas to Patrol within a Continuous Environment

The multi-agent patrolling problem consists of positioning agents to minimize the idleness, which represents the time difference between two visits of a same location by at least one agent.In the literature, these locations are defined manually by setting static nodes within a graph representation. However, in the context of patrolling a continuous environment, using static nodes cannot guarantee the coverage of the whole environment. In this article, we propose to discretize the continuous environment in order to generate dynamic waypoints called interest points (IP). We prove that these dynamic IP guarantee the coverage of the whole environment while dealing with its topography and the agent's observation range. We evaluated and compared our approach by benchmarking patrolling environment dealing with different observation ranges. Experiments show that dynamic IP locations are adaptive and more efficient to locate high idleness areas compared to static IP approach

Une architecture coopérative pour la localisation de cibles marines avec des véhicules sous-marins

There is a growing research interest in Autonomous Underwater Vehicles (AUV), due to the need for increasing our knowledge about the deep sea and understanding the effects the human way of life has on it. This need has pushed the development of new technologies to design more efficient and more autonomous underwater vehicles. Autonomy refers, in the context of this thesis, to the ''decisional autonomy'', i.e. the capability of taking decisions, in uncertain, varying and unknown environments. A more recent concern in AUV area is to consider a fleet of vehicles (AUV, ASV, etc). Indeed, multiple vehicles with heterogeneous capabilities have several advantages over a single vehicle system, and in particular the potential to accomplish tasks faster and better than a single vehicle. Underwater target localization using several AUVs (Autonomous Underwater Vehicles) is a challenging issue. A systematic and exhaustive coverage strategy is not efficient in term of exploration time: it can be improved by making the AUVs share their information and cooperate to optimize their motions. The contribution of this thesis is the definition of an architecture that integrates such a strategy that adapts each vehicle motions according to its and others' sensory information. Communication points are required to make underwater vehicles exchange information: for that purpose the system involves one ASV (Autonomous Surface Vehicle), that helps the AUVs re-localize and exchange data, and two AUVs that adapt their strategy according to gathered information, while satisfying the associated communication constraints. Each AUV is endowed with a sensor that estimates its distance with respect to targets, and cooperates with others to explore an area with the help of an ASV. To provide the required autonomy to these vehicles, we build upon an existing system (\texttt{T-REX}) with additional components, which provides an embedded planning and execution control framework. Simulation results ar e carried out to evaluate the proposed architecture and adaptive exploration strategy.Nous nous intéressons à l'architecture de robots marins et sous-marins autonomes dans le cadre de missions nécessitant leur coopération. Cette coopération s'avère difficile du fait que la communication (acoustique) est de faible qualité et de faible portée. Afin d'illustrer notre travail, nous nous intéressons à un scénario de localisation d'une source d'eau chaude sous-marine. Pour cela, le véhicule sous marin parcourt des segments de droite et rejoint des points de rendez-vous (points de communication). Ces derniers sont importants car ils permettent la mise en oeuvre d'une coopération entre les véhicules sous-marins. Au fur et à mesure du déplacement d'un véhicule, celui ci détecte (grâce à ses capteurs) sa distance à une zone pouvant contenir une source d'eau chaude. Afin de localiser une source, on doit permettre au véhicule de modifier sa trajectoire initiale, tout en s'assurant d'atteindre le point de rendez-vous. D'autre part, les rendez-vous permettent à chaque véhicule d'échanger ses données pour une coopération. Vu que le débit de communication acoustique est réduit, chaque véhicule doit extraire les informations utiles pour les communiquer. Nous présentons nos travaux effectués dans ce contexte, et une proposition d'architecture qui permet de trouver un compromis entre la modification de la trajectoire et l'atteinte de points de rendez-vous

An embedded testbed architecture to evaluate autonomous car driving

International audienc

An efficient cooperative exploration strategy for wireless sensor network

International audienc

Smart Communication for cooperative Wireless Sensor Network

Several embedded systems use Wireless Sensor Network (WSN) to monitor an area. However, efficient robust and reliable communication between sensors is hard to achieve. Thus, in this paper we focus on exploration area and we propose a new cooperative strategy. This strategy is based on Cognitive Radio (CR) and Software Defined Radio (SDR) that we consider as a “Smart Communication”. These radio systems search for a vacant spectrum band and reconfigures itself satisfying the requirements of any desired communication standard. Several simulation experiments demonstrate that the proposed approach improve exploration strategy

Autonomous Decisional High-level Planning for UAVs-based Forest-fire Localization

International audienc

A hybrid air-sea cooperative approach combined with a swarm trajectory planning method

This work addresses the issue of ocean monitoring and clean-up of polluted zones, as well as the notion of trajectory planning and fault tolerance for semi-autonomous unmanned vehicles. A hybrid approach for unmanned aerial vehicles (UAVs) is introduced to monitor the ocean region and cooperate with swarm of unmanned surface vehicles (USVs) to clean dirty zones. The paper proposes two solutions that apply to trajectory planning from the base of life to the dirty zone for swarm USVs. The first solution is performed by a modified Genetic Algorithm (GA), and the second uses a modified Ant Algorithm (AA). The proposed solutions were both implemented in the simulation with different scenarios for the dirty zone. This approach detects and reduces the pollution level in ocean zones while taking into account the problem of fault tolerance related to unmanned cleaning vehicles

A Centralized Architecture for Cooperative Air-Sea Vehicles Using UAV-USV

This paper deals with the problem of monitoring and cleaning dirty zones of oceans using unmanned vehicles. We present a centralized cooperative architecture for unmanned aerial vehicles (UAVs) to monitor ocean regions and clean dirty zones with the help of unmanned surface vehicles (USVs). Due to the rapid deployment of these unmanned vehicles, it is convenient to use them in oceanic regions where the water pollution zones are generally unknown. In order to optimize this process, our solution aims to detect and reduce the pollution level of the ocean zones while taking into account the problem of fault tolerance related to these vehicles