82 resultados para UNMANNED UNDERWATER VEHICLES
Resumo:
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
Resumo:
When underwater vehicles navigate close to the ocean floor, computer vision techniques can be applied to obtain motion estimates. A complete system to create visual mosaics of the seabed is described in this paper. Unfortunately, the accuracy of the constructed mosaic is difficult to evaluate. The use of a laboratory setup to obtain an accurate error measurement is proposed. The system consists on a robot arm carrying a downward looking camera. A pattern formed by a white background and a matrix of black dots uniformly distributed along the surveyed scene is used to find the exact image registration parameters. When the robot executes a trajectory (simulating the motion of a submersible), an image sequence is acquired by the camera. The estimated motion computed from the encoders of the robot is refined by detecting, to subpixel accuracy, the black dots of the image sequence, and computing the 2D projective transform which relates two consecutive images. The pattern is then substituted by a poster of the sea floor and the trajectory is executed again, acquiring the image sequence used to test the accuracy of the mosaicking system
Resumo:
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
Resumo:
Coverage Path Planning (CPP) is the task of determining a path that passes over all points of an area or volume of interest while avoiding obstacles. This task is integral to many robotic applications, such as vacuum cleaning robots, painter robots, autonomous underwater vehicles creating image mosaics, demining robots, lawn mowers, automated harvesters, window cleaners and inspection of complex structures, just to name a few. A considerable body of research has addressed the CPP problem. However, no updated surveys on CPP reflecting recent advances in the field have been presented in the past ten years. In this paper, we present a review of the most successful CPP methods, focusing on the achievements made in the past decade. Furthermore, we discuss reported field applications of the described CPP methods. This work aims to become a starting point for researchers who are initiating their endeavors in CPP. Likewise, this work aims to present a comprehensive review of the recent breakthroughs in the field, providing links to the most interesting and successful works
Resumo:
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
Resumo:
It is well known that image processing requires a huge amount of computation, mainly at low level processing where the algorithms are dealing with a great number of data-pixel. One of the solutions to estimate motions involves detection of the correspondences between two images. For normalised correlation criteria, previous experiments shown that the result is not altered in presence of nonuniform illumination. Usually, hardware for motion estimation has been limited to simple correlation criteria. The main goal of this paper is to propose a VLSI architecture for motion estimation using a matching criteria more complex than Sum of Absolute Differences (SAD) criteria. Today hardware devices provide many facilities for the integration of more and more complex designs as well as the possibility to easily communicate with general purpose processors
Resumo:
In this paper we describe a system for underwater navigation with AUVs in partially structured environments, such as dams, ports or marine platforms. An imaging sonar is used to obtain information about the location of planar structures present in such environments. This information is incorporated into a feature-based SLAM algorithm in a two step process: (I) the full 360deg sonar scan is undistorted (to compensate for vehicle motion), thresholded and segmented to determine which measurements correspond to planar environment features and which should be ignored; and (2) SLAM proceeds once the data association is obtained: both the vehicle motion and the measurements whose correct association has been previously determined are incorporated in the SLAM algorithm. This two step delayed SLAM process allows to robustly determine the feature and vehicle locations in the presence of large amounts of spurious or unrelated measurements that might correspond to boats, rocks, etc. Preliminary experiments show the viability of the proposed approach
Resumo:
This paper presents the distributed environment for virtual and/or real experiments for underwater robots (DEVRE). This environment is composed of a set of processes running on a local area network composed of three sites: 1) the onboard AUV computer; 2) a surface computer used as human-machine interface (HMI); and 3) a computer used for simulating the vehicle dynamics and representing the virtual world. The HMI can be transparently linked to the real sensors and actuators dealing with a real mission. It can also be linked with virtual sensors and virtual actuators, dealing with a virtual mission. The aim of DEVRE is to assist engineers during the software development and testing in the lab prior to real experiments
Resumo:
Nessie is an Autonomous Underwater Vehicle (AUV) created by a team of students in the Heriot Watt University to compete in the Student Autonomous Underwater Competition, Europe (SAUC-E) in August 2006. The main objective of the project is to find the dynamic equation of the robot, dynamic model. With it, the behaviour of the robot will be easier to understand and movement tests will be available by computer without the need of the robot, what is a way to save time, batteries, money and the robot from water inside itself. The object of the second part in this project is setting a control system for Nessie by using the model
Resumo:
This work proposes a parallel architecture for a motion estimation algorithm. It is well known that image processing requires a huge amount of computation, mainly at low level processing where the algorithms are dealing with a great numbers of data-pixel. One of the solutions to estimate motions involves detection of the correspondences between two images. Due to its regular processing scheme, parallel implementation of correspondence problem can be an adequate approach to reduce the computation time. This work introduces parallel and real-time implementation of such low-level tasks to be carried out from the moment that the current image is acquired by the camera until the pairs of point-matchings are detected
Resumo:
This work investigates performance of recent feature-based matching techniques when applied to registration of underwater images. Matching methods are tested versus different contrast enhancing pre-processing of images. As a result of the performed experiments for various dominating in images underwater artifacts and present deformation, the outperforming preprocessing, detection and description methods are proposed
Resumo:
Vehicle operations in underwater environments are often compromised by poor visibility conditions. For instance, the perception range of optical devices is heavily constrained in turbid waters, thus complicating navigation and mapping tasks in environments such as harbors, bays, or rivers. A new generation of high-definition forward-looking sonars providing acoustic imagery at high frame rates has recently emerged as a promising alternative for working under these challenging conditions. However, the characteristics of the sonar data introduce difficulties in image registration, a key step in mosaicing and motion estimation applications. In this work, we propose the use of a Fourier-based registration technique capable of handling the low resolution, noise, and artifacts associated with sonar image formation. When compared to a state-of-the art region-based technique, our approach shows superior performance in the alignment of both consecutive and nonconsecutive views as well as higher robustness in featureless environments. The method is used to compute pose constraints between sonar frames that, integrated inside a global alignment framework, enable the rendering of consistent acoustic mosaics with high detail and increased resolution. An extensive experimental section is reported showing results in relevant field applications, such as ship hull inspection and harbor mapping
Resumo:
Robotic platforms have advanced greatly in terms of their remote sensing capabilities, including obtaining optical information using cameras. Alongside these advances, visual mapping has become a very active research area, which facilitates the mapping of areas inaccessible to humans. This requires the efficient processing of data to increase the final mosaic quality and computational efficiency. In this paper, we propose an efficient image mosaicing algorithm for large area visual mapping in underwater environments using multiple underwater robots. Our method identifies overlapping image pairs in the trajectories carried out by the different robots during the topology estimation process, being this a cornerstone for efficiently mapping large areas of the seafloor. We present comparative results based on challenging real underwater datasets, which simulated multi-robot mapping
Resumo:
El procés de fusió de dues o més imatges de la mateixa escena en una d'única i més gran és conegut com a Image Mosaicing. Un cop finalitzat el procés de construcció d'un mosaic, els límits entre les imatges són habitualment visibles, degut a imprecisions en els registres fotomètric i geomètric. L'Image Blending és l'etapa del procediment de mosaicing a la que aquests artefactes són minimitzats o suprimits. Existeixen diverses metodologies a la literatura que tracten aquests problemes, però la majoria es troben orientades a la creació de panorames terrestres, imatges artístiques d'alta resolució o altres aplicacions a les quals el posicionament de la càmera o l'adquisició de les imatges no són etapes rellevants. El treball amb imatges subaquàtiques presenta desafiaments importants, degut a la presència d'scattering (reflexions de partícules en suspensió) i atenuació de la llum i a condicions físiques extremes a milers de metres de profunditat, amb control limitat dels sistemes d'adquisició i la utilització de tecnologia d'alt cost. Imatges amb il·luminació artificial similar, sense llum global com la oferta pel sol, han de ser unides sense mostrar una unió perceptible. Les imatges adquirides a gran profunditat presenten una qualitat altament depenent de la profunditat, i la seva degradació amb aquest factor és molt rellevant. El principal objectiu del treball és presentar dels principals problemes de la imatge subaquàtica, seleccionar les estratègies més adequades i tractar tota la seqüència adquisició-procesament-visualització del procés. Els resultats obtinguts demostren que la solució desenvolupada, basada en una Estratègia de Selecció de Límit Òptim, Fusió en el Domini del Gradient a les regions comunes i Emfatització Adaptativa d'Imatges amb baix nivell de detall permet obtenir uns resultats amb una alta qualitat. També s'ha proposat una estratègia, amb possibilitat d'implementació paral·lela, que permet processar mosaics de kilòmetres d'extensió amb resolució de centímetres per píxel.
Resumo:
Aquest projecte es centra en l’àmbit de l’automoció, i la seva finalitat es ampliar la informació que proporciona el fabricant d’un vehicle als usuaris. Un dels punts claus del sistema es que aquest quedi completament integrat, per tant, utilitza dispositius externs inclosos al vehicle com ara el display que anteriorment s’utilitzava per a mostrar informació del radiocasset, i una maneta amb dos botons utilitzada per al control del sistema. El sistema mostra diferents tipus d’informació com ara la velocitat instantània del vehicle, revolucions del motor, velocitat màxima, distància parcial recorreguda, hora i data. A més de mostrar informació, aquest es capaç d’emmagatzemar-la en un suport extraïble per a una posterior explotació a un ordinador convencional. El sistema no està pensat per a ser un projecte tancat, sinó que esta dissenyat per a ser ampliat en quant a funcionalitats, i per tant aquest projecte es considera una primera versió.