UC Riverside

The problem of an autonomous surface vehicle (ASV) optimally planning measurement locations to localize a set of pre-deployed acoustic underwater transponders (UTs) is considered. The ASV is assumed to make noisy range measurements to the UTs. A maximum a posteriori estimator is derived to localize the UTs. In addition, a multi-step look-ahead (MSLA) ASV optimal measurement location planning (OMLP) strategy is developed. This planning strategy prescribes future multi-step measurement locations. A physical interpretation of the proposed planner in the single-step, single transponder case is provided. Simulation results demonstrate the trade-off between expected localization performance and computational time associated with various look-ahead horizons and travel distances. Experimental results illustrate the proposed MSLA OMLP strategy's performance in environments containing one and two UTs. The proposed OMLP strategy is able to localize UTs to within 4 meters of their true locations. Additionally, increasing the planning horizon is demonstrated to yield better UT localization at the cost of increased computational burden.