Autonomous object identification in mine countermeasure missions

In this paper we present a planning algorithm for identification missions in an autonomous mine countermeasure scenario using AUVs. The concept of autonomous MCM identification missions is to first perform an autonomous survey of the mission area, during which an automatic target recognition (ATR) algorithm is run on the collected side-scan data. The ATR software detects possible contacts in the data, and classifies them as either clutter or a selection of mine classes. When the detection and classification are completed, the contact list is processed. In this processing contact with low detection confidence and classification confidence are discarded, while the rest are sent through a fusion process. In this process close contacts are fused together and their position averaged. After the contacts have been processed the list is sent to the identification planner. The identification planner will then create a mission plan with the goal of obtaining optical images of the reported contacts. To allow for deep water operation where surfacing for GPS position updates is impractical, and to allow for covert operations, HUGIN real-time terrain navigation is used, enabling the vehicle to update its navigation during the identification mission using a map created during the survey.