ROV Navigation with Mechanically Scanned Sonar and Inertial Sensors

The task of navigating a Remotely Operated underwater Vehicles (ROV) during inspection of man-made structures is performed mostly by visual references and occasionally a magnetic compass. Yet, some environments present a combination of low visibility and ferromagnetic anomalies that negates this approach. This paper, motivated by the development of a ROV designed to work on such environment, proposes a navigation method based on data from a mechanically scanned imaging sonar, a Doppler Velocity Log and a gyroscope, combined with prior information about the environment. To perform the data fusion, is used a particle filter that is a nonparametric implementation of the Bayes filter which estimate the states based on the sequential Monte Carlo method. The estimation of the position in this work was restricted to the horizontal plane because the development of the ROV is in the initial stage and so a floating platform was used in its place (since ROVs are usually statically stable on pitch and roll, this is a good approximation). The tests were conducted in a rectangular tank of know size, and the results shows that the propose navigation system can estimates planar position of the vehicle with great precision