L’épave du Machault, 1760 : entre tradition et innovation.

Cette étude s’intéresse à l’industrie de la construction navale pour le milieu du XVIIIe siècle en France dans la région de Bayonne. L’objectif est de documenter la relation qu’entretiennent les pratiques de construction traditionnelles et innovatrices à cette période. L’architecture de la frégate le Machault est au cœur de cette analyse. Construit en 1757 à Bayonne et perdu en 1760, le Machault a été fouillé, documenté et parallèlement récupéré par les archéologues de Parcs Canada entre 1969 et 1972 à Ristigouche dans la baie des Chaleurs, Québec. Cette étude constitue la première analyse architecturale approfondie menée sur ces vestiges. L’analyse est réalisée en trois temps qui correspondent aux trois grandes étapes de la chaine opératoire de la construction du navire. Tout d’abord, il est question d’aborder l’aspect de la foresterie afin de saisir la nature de la ressource forestière mobilisée pour la construction de la frégate. Ensuite, ce mémoire se penche sur la conception architecturale des navires qui renvoie à un aspect plus théorique, car il relève de la façon dont les formes du navire ont été « pensées ». Enfin, la charpenterie est abordée afin de saisir la séquence d’assemblage du navire. Ensemble, ces trois grands aspects dressent un portrait général de la construction navale pour la région de Bayonne au milieu du XVIIIe siècle.

L’épave du Machault, 1760 : entre tradition et innovation

Cette étude s’intéresse à l’industrie de la construction navale pour le milieu du XVIIIe siècle en France dans la région de Bayonne. L’objectif est de documenter la relation qu’entretiennent les pratiques de construction traditionnelles et innovatrices à cette période. L’architecture de la frégate le Machault est au cœur de cette analyse. Construit en 1757 à Bayonne et perdu en 1760, le Machault a été fouillé, documenté et parallèlement récupéré par les archéologues de Parcs Canada entre 1969 et 1972 à Ristigouche dans la baie des Chaleurs, Québec. Cette étude constitue la première analyse architecturale approfondie menée sur ces vestiges. L’analyse est réalisée en trois temps qui correspondent aux trois grandes étapes de la chaine opératoire de la construction du navire. Tout d’abord, il est question d’aborder l’aspect de la foresterie afin de saisir la nature de la ressource forestière mobilisée pour la construction de la frégate. Ensuite, ce mémoire se penche sur la conception architecturale des navires qui renvoie à un aspect plus théorique, car il relève de la façon dont les formes du navire ont été « pensées ». Enfin, la charpenterie est abordée afin de saisir la séquence d’assemblage du navire. Ensemble, ces trois grands aspects dressent un portrait général de la construction navale pour la région de Bayonne au milieu du XVIIIe siècle.

Lusitanian Amphorae on Western Mediterranean Shipwrecks: Fragments of Economic History

Shipwrecks constitute a primary source for the study of the ancient economy. In this paper, we will highlight some of those whose cargo contained amphorae of Lusitanian production. These are of the utmost importance for understanding the navigation routes and the Lusitanian fish products export routes in the western Mediterranean.

A Vision Based Target Detection System for Docking of an Autonomous Underwater Vehicle

This paper describes the development and preliminary experimental evaluation of a visionbased docking system to allow an Autonomous Underwater Vehicle (AUV) to identify and attach itself to a set of uniquely identifiable targets. These targets, docking poles, are detected using Haar rectangular features and rotation of integral images. A non-holonomic controller allows the Starbug AUV to orient itself with respect to the target whilst maintaining visual contact during the manoeuvre. Experimental results show the proposed vision system is capable of robustly identifying a pair of docking poles simultaneously in a variety of orientations and lighting conditions. Experiments in an outdoor pool show that this vision system enables the AUV to dock autonomously from a distance of up to 4m with relatively low visibility.

Data muling over underwater wireless sensor networks using an autonomous underwater vehicle

We present algorithms, systems, and experimental results for underwater data muling. In data muling a mobile agent interacts with static agents to upload, download, or transport data to a different physical location. We consider a system comprising an Autonomous Underwater Vehicle (AUV) and many static Underwater Sensor Nodes (USN) networked together optically and acoustically. The AUV can locate the static nodes using vision and hover above the static nodes for data upload. We describe the hardware and software architecture of this underwater system, as well as experimental data. © 2006 IEEE.

Krill: An exploration in underwater sensor networks

While sensor networks have now become very popular on land, the underwater environment still poses some difficult problems. Communication is one of the difficult challenges under water. There are two options: optical and acoustic. We have designed an optical communication board that allows the Fleck’s to communicate optically. We have tested the resulting underwater sensor nodes in two different applications.

Experiments with cooperative networked control of underwater robots

We present details and results obtained with an underwater system comprising two different autonomous underwater robots (AUV) and ten static underwater nodes (USN) networked together optically and acoustically. The AUVs can locate and hover above the static nodes for data upload, and they can perform network maintenance functions such as deployment, relocation, and recovery. The AUVs can also locate each other, dock, and move using coordinated control that takes advantage of each AUV’s strength.

Experiments with underwater robot localization and tracking

This paper describes a novel experiment in which two very different methods of underwater robot localization are compared. The first method is based on a geometric approach in which a mobile node moves within a field of static nodes, and all nodes are capable of estimating the range to their neighbours acoustically. The second method uses visual odometry, from stereo cameras, by integrating scaled optical flow. The fundamental algorithmic principles of each localization technique is described. We also present experimental results comparing acoustic localization with GPS for surface operation, and a comparison of acoustic and visual methods for underwater operation.

Visual motion estimation for an autonomous underwater reef monitoring robot

Performing reliable localisation and navigation within highly unstructured underwater coral reef environments is a difficult task at the best of times. Typical research and commercial underwater vehicles use expensive acoustic positioning and sonar systems which require significant external infrastructure to operate effectively. This paper is focused on the development of a robust vision-based motion estimation technique using low-cost sensors for performing real-time autonomous and untethered environmental monitoring tasks in the Great Barrier Reef without the use of acoustic positioning. The technique is experimentally shown to provide accurate odometry and terrain profile information suitable for input into the vehicle controller to perform a range of environmental monitoring tasks.

Visual motion estimation for an autonomous underwater reef monitoring robot

Performing reliable localisation and navigation within highly unstructured underwater coral reef environments is a difficult task at the best of times. Typical research and commercial underwater vehicles use expensive acoustic positioning and sonar systems which require significant external infrastructure to operate effectively. This paper is focused on the development of a robust vision-based motion estimation technique using low-cost sensors for performing real-time autonomous and untethered environmental monitoring tasks in the Great Barrier Reef without the use of acoustic positioning. The technique is experimentally shown to provide accurate odometry and terrain profile information suitable for input into the vehicle controller to perform a range of environmental monitoring tasks.

Data collection, storage and retrieval with an underwater sensor network

In this paper we present a novel platform for underwater sensor networks to be used for long-term monitoring of coral reefs and �sheries. The sensor network consists of static and mobile underwater sensor nodes. The nodes communicate point-to-point using a novel high-speed optical communication system integrated into the TinyOS stack, and they broadcast using an acoustic protocol integrated in the TinyOS stack. The nodes have a variety of sensing capabilities, including cameras, water temperature, and pressure. The mobile nodes can locate and hover above the static nodes for data muling, and they can perform network maintenance functions such as deployment, relocation, and recovery. In this paper we describe the hardware and software architecture of this underwater sensor network. We then describe the optical and acoustic networking protocols and present experimental networking and data collected in a pool, in rivers, and in the ocean. Finally, we describe our experiments with mobility for data muling in this network.

Experiments in visual localisation around underwater structures

Localisation of an AUV is challenging and a range of inspection applications require relatively accurate positioning information with respect to submerged structures. We have developed a vision based localisation method that uses a 3D model of the structure to be inspected. The system comprises a monocular vision system, a spotlight and a low-cost IMU. Previous methods that attempt to solve the problem in a similar way try and factor out the effects of lighting. Effects, such as shading on curved surfaces or specular reflections, are heavily dependent on the light direction and are difficult to deal with when using existing techniques. The novelty of our method is that we explicitly model the light source. Results are shown of an implementation on a small AUV in clear water at night.

Persistent ocean monitoring with underwater gliders : towards accurate reconstruction of dynamic ocean processes

Ocean processes are dynamic and complex events that occur on multiple different spatial and temporal scales. To obtain a synoptic view of such events, ocean scientists focus on the collection of long-term time series data sets. Generally, these time series measurements are continually provided in real or near-real time by fixed sensors, e.g., buoys and moorings. In recent years, an increase in the utilization of mobile sensor platforms, e.g., Autonomous Underwater Vehicles, has been seen to enable dynamic acquisition of time series data sets. However, these mobile assets are not utilized to their full capabilities, generally only performing repeated transects or user-defined patrolling loops. Here, we provide an extension to repeated patrolling of a designated area. Our algorithms provide the ability to adapt a standard mission to increase information gain in areas of greater scientific interest. By implementing a velocity control optimization along the predefined path, we are able to increase or decrease spatiotemporal sampling resolution to satisfy the sampling requirements necessary to properly resolve an oceanic phenomenon. We present a path planning algorithm that defines a sampling path, which is optimized for repeatability. This is followed by the derivation of a velocity controller that defines how the vehicle traverses the given path. The application of these tools is motivated by an ongoing research effort to understand the oceanic region off the coast of Los Angeles, California. The computed paths are implemented with the computed velocities onto autonomous vehicles for data collection during sea trials. Results from this data collection are presented and compared for analysis of the proposed technique.