Xevi Cufí

Positioning an underwater vehicle through image mosaicking

Mosaics have been commonly used as visual maps for undersea exploration and navigation. The position and orientation of an underwater vehicle can be calculated by integrating the apparent motion of the images which form the mosaic. A feature-based mosaicking method is proposed in this paper. The creation of the mosaic is accomplished in four stages: feature selection and matching, detection of points describing the dominant motion, homography computation and mosaic construction. In this work we demonstrate that the use of color and textures as discriminative properties of the image can improve, to a large extent, the accuracy of the constructed mosaic. The system is able to provide 3D metric information concerning the vehicle motion using the knowledge of the intrinsic parameters of the camera while integrating the measurements of an ultrasonic sensor. The experimental results of real images have been tested on the GARBI underwater vehicle.

On the way to solve lighting problems in underwater imaging

A major obstacle to processing images of the ocean floor comes from the absorption and scattering effects of the light in the aquatic environment. Due to the absorption of the natural light, underwater vehicles often require artificial light sources attached to them to provide the adequate illumination. Unfortunately, these flashlights tend to illuminate the scene in a nonuniform fashion, and, as the vehicle moves, induce shadows in the scene. For this reason, the first step towards application of standard computer vision techniques to underwater imaging requires dealing first with these lighting problems. This paper analyses and compares existing methodologies to deal with low-contrast, nonuniform illumination in underwater image sequences. The reviewed techniques include: (i) study of the illumination-reflectance model, (ii) local histogram equalization, (iii) homomorphic filtering, and, (iv) subtraction of the illumination field. Several experiments on real data have been conducted to compare the different approaches.

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.

Image Mosaicking for Estimating the Motion of an Underwater Vehicle

A composite image constructed by combining a set of smaller images is known as mosaic. Mosaics of the ocean floor are very useful in undersea exploration, creation of visual maps, navigation, etc. A feature-based mosaicking method is proposed, based on textural parameters of certain parts of the image. Textures significantly help in the identification of given features of the image. The tracking of these features over time solves the matching problem in consecutive frames. The correspondence is established with the aid of a cross-correlation algorithm, applied to the colour components of the image in the HSI space. Once the correspondence has been found a displacement vector is obtained relating the features of two images of the sequence. The motion parameters between consecutive frames are estimated through an error minimisation technique. Once the best transformation between two frames has been found, images are warped together composing the mosaic, and information about the vehicle motion is recovered. The experimental results on real images show the effectiveness of the proposed method. Copyright  2000 IFAC

Calibration of optical camera coupled to acoustic multibeam for underwater 3D scene reconstruction

Combination of optical and acoustic sensors to compensate the strengths and weaknesses of each sensor modality is a topic of increasing interest in applications involving autonomous underwater vehicles (AUV). In this work, an opti-acoustic system composed by a single camera and a multibeam sonar is proposed, providing a simulation environment to validate its potential use in 3D reconstruction. Since extrinsic calibration is a prerequisite for this kind of feature-level sensor fusion, an effective approach to address the calibration problem between a multibeam and a camera is presented.

A system to evaluate the accuracy of a visual mosaicking methodology

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.

Attracting talent to increase interest for engineering among secondary school students

This paper reports our experience in developing a team-based project activity to promote engineering programs among secondary school students. The aim of the activity is to increase the interest of students for science and technology in general, but also to promote engineering skills, capabilities and values, leading to attract more secondary school students to enrollment for engineering programs. Simple theoretical concepts are illustrated through hands-on experimentation. To achieve this goal, the students build a Remotely Operated Underwater Robot in a 2½-day workshop. The robot is built using low-cost materials and the students customize their own design over the different phases of the workshop. Once the activity is completed, every team understands that with teamwork, effort and a good working strategy, every problem can be overcome. At the end of the activity, a survey is conducted through an assessment survey questionnaire which reflects different aspects related with the development of the activity and the degree to which learning of its different facets has been achieved. The responses and feedback from students serve not only to evaluate the workshop, but also as feedback for future fine-tuning of the different phases as pedagogical learning tools.

Embedding range information in omnidirectional images through laser range finder

Robot map navigation and localization are challenging tasks that require the solving of the data association problem for local and global features. Data fusion allows the advantages of two or more sensors to be combined, and complementary cooperation can be obtained. This paper presents two methods to embed depth information in omnidirectional images using the extrinsic calibration of a 2D laser range finder and a central catadioptric camera. The methods presented do not require a visible laser beam, but they assume the planar checkerboard patterns are visible for both the catadioptric camera and the 2D laser range finder. Unlike other approaches, the methods proposed used an invisible laser trace, and they are evaluated at pixel error level using ground truth data from the calibration patterns projected in the omnidirectional image. Results include a mean square error analysis of all calibration poses, and laser point projection on indoor omnidirectional images. We think that embedding range information in omnidirectional images is an interesting tool for data fusion approaches, which can be used in robot map building and localization.

An EKF vision-based navigation of an UUV in a structured environment

Abstract This paper presents a vision-based navigation system for an underwater robot in a structured environment. The system is based in a coded pattern placed on the bottom of a water tank and an onboard down looking camera. The system provides three dimensional position and orientation of the vehicle. Accuracy of the drift-free estimate of the position is very high, with low noise effects. An extended Kalman filter based on the dynamic model of the robot is used to improve position and velocity estimation.

AUV Navigation in a Structured Environment Using Computer Vision

Abstract This paper presents a vision-based navigation 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 navigation, landmark detection and tracking, and real-tirne computation (12.5 Hz). The proposed system proyides three-dirnensional 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 navigation algorithm and shows some results.