Seguiment temporal de les àrees protegides del Cap de Creus, del Montgrí i de les Illes Medes

Els fons rocosos del litoral català són d'una immensa varietat biogeogràfica. La Costa Brava i especialmentles àrees que interessen aquest estudi, presenten una morfologia molt variada amb fons de roca i desediments que ofereixen una amplíssima riquesa d'hàbitats i de comunitats d'animals i vegetals submarins. L'explotació continuada d'aquests indrets tant a nivell pesquer com turístic, ha deixat la seva empremta, especialment en les comunitats de peixos. Malgrat tot, la dinàmica de recuperació de les poblacions d'algunes espècies, com ara el mero, evidencia molt marcadament un abans i un després la implementació de mesures de protecció en aquests indrets.

L’estatge infralitoral de la costa del Montgrí i les illes Medes: comunitats algals i poblacions de garotes

Les algues són els organismes que dominen la majoria de paisatges submarins bentònics. De fet, les algues són presents a totes les comunitats bentòniques del nostre litoral, des de la superfície del mar finsa fondàries que poden superar els 100 metres. Tot i que agrupem les algues en un gran grup genèric, es tracta en realitat d’un conjunt molt heterogeni, amb una gran quantitat d’espècies que tenen característiques molt diferents entre elles, amb requeriments fisiològics i resposta a les condicions ambientals tambédiferents i que condicionen la seva distribució. Així, cada espècie s’ha adaptat a viure en un ambient amb unes condicions determinades d’il·luminació, hidrodinamisme i disponibilitat de nutrients, tipus desubstrat o temperatura (Ollivier, 1929; Feldmann, 1937; Péres i Picard, 1964; Riedl, 1966; Ros et al., 1985). Com a resultat d’aquesta sèrie de factors ambientals, que segueixen essencialment un gradient batimètric, podem observar una marcada zonació, de forma que cada espècie o comunitat només és present enun rang de profunditats determinat. D’aquesta forma, en el litoral marí trobem un paisatge organitzat en bandes horitzontals; aquestes bandes poden assimilar-se a diferents tipus de comunitats.

Avaluació dels canvis de ritme de sedimentació en el canyó submarí d'Arenys a partir del Pb-210

Amb la finalitat d’estudiar els ritmes d’acumulació de sediments durant els últims 100 anys, s’han extret tres testimonis de sediments del canyó d’Arenys a profunditats de 1074 m, 1410 m i 1632 m respectivament. Els ritmes de sedimentació basats en els perfils verticals de Pb-210 suggereixen que les tendències actuals sobre el flux i acumulació de sediments poden ser diferents a tendències passades. Durant la dècada dels 70 es va portar a terme una ràpida evolució de la flota pesquera del port d’Arenys de Mar. Aquest fet es pot relacionar amb els canvis en el ritme d’acumulació dels sediments al testimoni extret a 1074 m. Els flancs del canyó submarí són objectiu dels arrossegadors del port d’Arenys de Mar, una activitat que pot fer variar la morfologia del fons marí, la resuspensió de les partícules i pot crear fluxos de terbolesa. Per tant, els resultats suggereixen que l’activitat pesquera d’arrossegament pot afectar als ambients submarins d’una manera més important del que s’havia pensat.

Augmented state Kalman filtering for AUV navigation

Addresses the problem of estimating the motion of an autonomous underwater vehicle (AUV), while it constructs a visual map ("mosaic" image) of the ocean floor. The vehicle is equipped with a down-looking camera which is used to compute its motion with respect to the seafloor. As the mosaic increases in size, a systematic bias is introduced in the alignment of the images which form the mosaic. Therefore, this accumulative error produces a drift in the estimation of the position of the vehicle. When the arbitrary trajectory of the AUV crosses over itself, it is possible to reduce this propagation of image alignment errors within the mosaic. A Kalman filter with augmented state is proposed to optimally estimate both the visual map and the vehicle position

Visual SLAM for 3D large-scale seabed acquisition employing underwater vehicles

This paper presents a novel technique to align partial 3D reconstructions of the seabed acquired by a stereo camera mounted on an autonomous underwater vehicle. Vehicle localization and seabed mapping is performed simultaneously by means of an Extended Kalman Filter. Passive landmarks are detected on the images and characterized considering 2D and 3D features. Landmarks are re-observed while the robot is navigating and data association becomes easier but robust. Once the survey is completed, vehicle trajectory is smoothed by a Rauch-Tung-Striebel filter obtaining an even better alignment of the 3D views and yet a large-scale acquisition of the seabed

Visual SLAM for underwater vehicles using video velocity log and natural landmarks

A visual SLAM system has been implemented and optimised for real-time deployment on an AUV equipped with calibrated stereo cameras. The system incorporates a novel approach to landmark description in which landmarks are local sub maps that consist of a cloud of 3D points and their associated SIFT/SURF descriptors. Landmarks are also sparsely distributed which simplifies and accelerates data association and map updates. In addition to landmark-based localisation the system utilises visual odometry to estimate the pose of the vehicle in 6 degrees of freedom by identifying temporal matches between consecutive local sub maps and computing the motion. Both the extended Kalman filter and unscented Kalman filter have been considered for filtering the observations. The output of the filter is also smoothed using the Rauch-Tung-Striebel (RTS) method to obtain a better alignment of the sequence of local sub maps and to deliver a large-scale 3D acquisition of the surveyed area. Synthetic experiments have been performed using a simulation environment in which ray tracing is used to generate synthetic images for the stereo system

Immersió!

Vint-i-un estudiants de l'IES Castell d'Estela d'Amer han participat durant tres dies en una experiència de recerca amb els investigadors del centre ViCOROB de la UdG

An hybrid methodology for RL-based behavior coordination in a target following mission with an AUV

Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

Vision-based localization of an underwater robot in a structured environment

This paper presents a vision-based localization approach for an underwater robot in a structured environment. The system is based on a coded pattern placed on the bottom of a water tank and an onboard down looking camera. Main features are, absolute and map-based localization, landmark detection and tracking, and real-time computation (12.5 Hz). The proposed system provides three-dimensional position and orientation of the vehicle along with its velocity. Accuracy of the drift-free estimates is very high, allowing them to be used as feedback measures of a velocity-based low-level controller. The paper details the localization algorithm, by showing some graphical results, and the accuracy of the system

Estimating the motion of an underwater robot from a monocular image sequence

When underwater vehicles perform navigation close to the ocean floor, computer vision techniques can be applied to obtain quite accurate motion estimates. The most crucial step in the vision-based estimation of the vehicle motion consists on detecting matchings between image pairs. Here we propose the extensive use of texture analysis as a tool to ameliorate the correspondence problem in underwater images. Once a robust set of correspondences has been found, the three-dimensional motion of the vehicle can be computed with respect to the bed of the sea. Finally, motion estimates allow the construction of a map that could aid to the navigation of the robot

Towards a real-time vision-based navigation system for a small-class UUV

This paper deals with the problem of navigation for an unmanned underwater vehicle (UUV) through image mosaicking. It represents a first step towards a real-time vision-based navigation system for a small-class low-cost UUV. We propose a navigation system composed by: (i) an image mosaicking module which provides velocity estimates; and (ii) an extended Kalman filter based on the hydrodynamic equation of motion, previously identified for this particular UUV. The obtained system is able to estimate the position and velocity of the robot. Moreover, it is able to deal with visual occlusions that usually appear when the sea bottom does not have enough visual features to solve the correspondence problem in a certain area of the trajectory

Augmented state Kalman filtering for AUV navigation

Addresses the problem of estimating the motion of an autonomous underwater vehicle (AUV), while it constructs a visual map ("mosaic" image) of the ocean floor. The vehicle is equipped with a down-looking camera which is used to compute its motion with respect to the seafloor. As the mosaic increases in size, a systematic bias is introduced in the alignment of the images which form the mosaic. Therefore, this accumulative error produces a drift in the estimation of the position of the vehicle. When the arbitrary trajectory of the AUV crosses over itself, it is possible to reduce this propagation of image alignment errors within the mosaic. A Kalman filter with augmented state is proposed to optimally estimate both the visual map and the vehicle position

Probabilistic sonar scan matching for an AUV

This paper proposes MSISpIC, a probabilistic sonar scan matching algorithm for the localization of an autonomous underwater vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), the robot displacement estimated through dead-reckoning using a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method is an extension of the pIC algorithm. An extended Kalman filter (EKF) is used to estimate the robot-path during the scan in order to reference all the range and bearing measurements as well as their uncertainty to a scan fixed frame before registering. The major contribution consists of experimentally proving that probabilistic sonar scan matching techniques have the potential to improve the DVL-based navigation. The algorithm has been tested on an AUV guided along a 600 m path within an abandoned marina underwater environment with satisfactory results

Dam wall detection and tracking using a Mechanically Scanned Imaging Sonar

In dam inspection tasks, an underwater robot has to grab images while surveying the wall meanwhile maintaining a certain distance and relative orientation. This paper proposes the use of an MSIS (mechanically scanned imaging sonar) for relative positioning of a robot with respect to the wall. An imaging sonar gathers polar image scans from which depth images (range & bearing) are generated. Depth scans are first processed to extract a line corresponding to the wall (with the Hough transform), which is then tracked by means of an EKF (Extended Kalman Filter) using a static motion model and an implicit measurement equation associating the sensed points to the candidate line. The line estimate is referenced to the robot fixed frame and represented in polar coordinates (rho&thetas) which directly corresponds to the actual distance and relative orientation of the robot with respect to the wall. The proposed system has been tested in simulation as well as in water tank conditions