Underwater navigation using egomotion estimates

The goal of this work is to propose a method to solve the problem of underwater navigation of an autonomous vehicle with visual means. We refer to the ability of an autonomous system to determine its motion with respect to the environment. The method we propose is a two stage approach: matching of features extracted from 2D images acquired at different times and egomotion parameter computation. Both algorithms are based on optimization approaches minimizing appropriate energy functions. The matching stage recovers correspondences between sparse high interest feature points of two successive images useful to perform the second stage of egomotion parameter estimation. Experimental results obtained in real context show the robustness of the method.