Supervised navigation: optimal algorithm example and needs for autonomous supervision

This paper presents an algorithm which allows an AUV to reset its localization (position and orientation) and to estimate the water current while moving in the vicinity of two acoustic beacons. The algorithm is based on a Kalman filter which integrates the measurements provided by an ultra short base line array located in the vehicle, a Doppler log, a depthmeter and an attitude and heading reference system. After such an estimation phase, the vehicle can start to dead reckon away from the beacons in the best conditions and come back for a reset when necessary. Various considerations about the algorithm allow us to introduce the concept of `navigation supervisor´ currently under development at IFREMER. This study is conducted based on the work previously done for implementation of high-level intelligent control and mission programming