Abstract (EN):
This article concerns an approach for cooperative plume tracing in an underwater environment characterized by very strict communication constraints such as delays, low reliability and limited bandwidth, as well as by the absence of natural features which would help localization and navigation. Localization is of utmost importance for plume tracing and remains a challenging area for AUVs in such a difficult environment. The adopted approach requires only relative localization which is satisfactorily achieved by using a SLAM-like scheme based on Extended Kalman Filter that takes into account the communications constraints. In this scheme, for any given AUV, the other elements of the team play the role of "environmental" features of a dynamic nature. The vehicles share data - relative localization as well as plume samples data - in order to improve localization estimates and generate motion waypoints according to the well known simplex algorithm. Since in this case the vertices are given by vehicle position estimates, they will have some associated uncertainty. We analyse under what conditions the simplex with uncertain vertices reduces to the regular simplex, and simulations reveal that the uncertainty of the adopted cooperative localization method suffices to ensure that the simplex algorithm "converges" to an estimate of the plume source.
Language:
English
Type (Professor's evaluation):
Scientific
No. of pages:
6