Observability Based Path Planning in Range-only Localization

Abstract

The motivations of oceanographic research have driven the development of autonomous underwater vehicles (AUVs) now capable of great feats of autonomy and endurance. It is anticipated that the future of autonomous oceanographic surveys will be conducted with mixed teams of vehicles that will reduce cost and improve data quality. In a commonly proposed scenario, a scientific survey is carried out by a group of low-cost, simplistic AUVs while a more capable vehicle tends to the group; providing communication and navigation assistance. The goal of this thesis is to explore path planning methods for the aid vehicle that aim to improve localization performance experienced by survey vehicles. The two planning methods proposed make use of local observability measures to decide an aid vehicle's steering control. Simulations are conducted to test both methods against typical survey missions to investigate their efficacy in improving localization performance.