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

A parallel hypothesis method of autonomous underwater vehicle 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 June 2009This research presents a parallel hypothesis method for autonomous underwater vehicle navigation that enables a vehicle to expand the operating envelope of existing long baseline acoustic navigation systems by incorporating information that is not normally used. The parallel hypothesis method allows the in-situ identification of acoustic multipath time-of-flight measurements between a vehicle and an external transponder and uses them in real-time to augment the navigation algorithm during periods when direct-path time-of-flight measurements are not available. A proof of concept was conducted using real-world data obtained by the Woods Hole Oceanographic Institution Deep Submergence Lab's Autonomous Benthic Explorer (ABE) and Sentry autonomous underwater vehicles during operations on the Juan de Fuca Ridge. This algorithm uses a nested architecture to break the navigation solution down into basic building blocks for each type of available external information. The algorithm classifies external information as either line of position or gridded observations. For any line of position observation, the algorithm generates a multi-modal block of parallel position estimate hypotheses. The multimodal hypotheses are input into an arbiter which produces a single unimodal output. If a priori maps of gridded information are available, they are used within the arbiter structure to aid in the elimination of false hypotheses. For the proof of concept, this research uses ranges from a single external acoustic transponder in the hypothesis generation process and grids of low-resolution bathymetric data from a ship-based multibeam sonar in the arbitration process. The major contributions of this research include the in-situ identification of acoustic multipath time-of-flight measurements, the multiscale utilization of a priori low-resolution bathymetric data in a high-resolution navigation algorithm, and the design of a navigation algorithm with a exible architecture. This flexible architecture allows the incorporation of multimodal beliefs without requiring a complex mechanism for real-time hypothesis generation and culling, and it allows the real-time incorporation of multiple types of external information as they become available in situ into the overall navigation solution

Feature relative navigation for automous underwater vehicles

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering, 1997.Includes bibliographical references (leaves 184-196).by Andrew Arnold Bennett.Ph.D