Augmented state Kalman filtering for AUV navigation

This paper 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.

Using Linear Features for Aerial Image Sequence Mosaiking

With recent advances in sensor technology and digital image processing techniques, automatic image mosaicking has received increased attention in a variety of geospatial applications, ranging from panorama generation and video surveillance to image based rendering. The geometric transformation used to link images in a mosaic is the subject of image orientation, a fundamental photogrammetric task that represents a major research area in digital image analysis. It involves the determination of the parameters that express the location and pose of a camera at the time it captured an image. In aerial applications the typical parameters comprise two translations (along the x and y coordinates) and one rotation (rotation about the z axis). Orientation typically proceeds by extracting from an image control points, i.e. points with known coordinates. Salient points such as road intersections, and building corners are commonly used to perform this task. However, such points may contain minimal information other than their radiometric uniqueness, and, more importantly, in some areas they may be impossible to obtain (e.g. in rural and arid areas). To overcome this problem we introduce an alternative approach that uses linear features such as roads and rivers for image mosaicking. Such features are identified and matched to their counterparts in overlapping imagery. Our matching approach uses critical points (e.g. breakpoints) of linear features and the information conveyed by them (e.g. local curvature values and distance metrics) to match two such features and orient the images in which they are depicted. In this manner we orient overlapping images by comparing breakpoint representations of complete or partial linear features depicted in them. By considering broader feature metrics (instead of single points) in our matching scheme we aim to eliminate the effect of erroneous point matches in image mosaicking. Our approach does not require prior approximate parameters, which are typically an essential requirement for successful convergence of point matching schemes. Furthermore, we show that large rotation variations about the z-axis may be recovered. With the acquired orientation parameters, image sequences are mosaicked. Experiments with synthetic aerial image sequences are included in this thesis to demonstrate the performance of our approach

Imaging sensors in underwaters robotics: present and future trends

The two main visual sensors in underwater robotics are sonar and video. In a first part, we present the fundamentals of acoustic imagery. If some technics are well known, others, like synthetic aperture antenna, interferometry and parametric array are still research topics. In a second part, acoustic image processing techniques are presented. They are mainly applied to sea bottom characterization and robot navigation. The third part addresses video technology and processing. This sensor is complementary to sonar, due to its high resolution and the ease of interpretation of the images.Les deux principaux instruments utilisés comme capteurs de perception en robotique sous-marine sont le sonar et la vidéo. Dans une première partie, nous présentons les principes utilisés en imagerie acoustique. Si certaines techniques sont classiques, d'autres, telles que l'antenne synthétique, l'interférométrie et l'antenne paramétrique sont encore du domaine de la recherche appliquée. Dans une seconde partie, les applications de l'imagerie acoustique sont évoquées. Elles sont essentiellement axées sur la caractérisation des fonds sous-marins et sur l'aide que l'image peut apporter à la navigation du robot. Enfin, la troisième partie évoque les technologies et les traitements vidéo. Ce capteur s'avère très complémentaire du sonar grâce à sa haute résolution et à la facilité d'interprétation des images

Contributions to automated realtime underwater navigation

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2012This dissertation presents three separate–but related–contributions to the art of underwater navigation. These methods may be used in postprocessing with a human in the loop, but the overarching goal is to enhance vehicle autonomy, so the emphasis is on automated approaches that can be used in realtime. The three research threads are: i) in situ navigation sensor alignment, ii) dead reckoning through the water column, and iii) model-driven delayed measurement fusion. Contributions to each of these areas have been demonstrated in simulation, with laboratory data, or in the field–some have been demonstrated in all three arenas. The solution to the in situ navigation sensor alignment problem is an asymptotically stable adaptive identifier formulated using rotors in Geometric Algebra. This identifier is applied to precisely estimate the unknown alignment between a gyrocompass and Doppler velocity log, with the goal of improving realtime dead reckoning navigation. Laboratory and field results show the identifier performs comparably to previously reported methods using rotation matrices, providing an alignment estimate that reduces the position residuals between dead reckoning and an external acoustic positioning system. The Geometric Algebra formulation also encourages a straightforward interpretation of the identifier as a proportional feedback regulator on the observable output error. Future applications of the identifier may include alignment between inertial, visual, and acoustic sensors. The ability to link the Global Positioning System at the surface to precision dead reckoning near the seafloor might enable new kinds of missions for autonomous underwater vehicles. This research introduces a method for dead reckoning through the water column using water current profile data collected by an onboard acoustic Doppler current profiler. Overlapping relative current profiles provide information to simultaneously estimate the vehicle velocity and local ocean current–the vehicle velocity is then integrated to estimate position. The method is applied to field data using online bin average, weighted least squares, and recursive least squares implementations. This demonstrates an autonomous navigation link between the surface and the seafloor without any dependence on a ship or external acoustic tracking systems. Finally, in many state estimation applications, delayed measurements present an interesting challenge. Underwater navigation is a particularly compelling case because of the relatively long delays inherent in all available position measurements. This research develops a flexible, model-driven approach to delayed measurement fusion in realtime Kalman filters. Using a priori estimates of delayed measurements as augmented states minimizes the computational cost of the delay treatment. Managing the augmented states with time-varying conditional process and measurement models ensures the approach works within the proven Kalman filter framework–without altering the filter structure or requiring any ad-hoc adjustments. The end result is a mathematically principled treatment of the delay that leads to more consistent estimates with lower error and uncertainty. Field results from dead reckoning aided by acoustic positioning systems demonstrate the applicability of this approach to real-world problems in underwater navigation.I have been financially supported by: the National Defense Science and Engineering Graduate (NDSEG) Fellowship administered by the American Society for Engineering Education, the Edwin A. Link Foundation Ocean Engineering and Instrumentation Fellowship, and WHOI Academic Programs office

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 vehicl

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties