On AUV actions to correctly label world information

Abstract

Abstract-An Autonomous Underwater Vehicle (AUV) needs to demonstrate a number of capabilities, in order to carry on autonomous missions with success. One of the key areas is correctly understanding the surrounding environment. However, most of the state-of-the-art approaches in labelling world information are based on the analysis of a single frame, whilst -especially in scenarios where the vehicle interact with complex structuresthere is the need of sensor data from multiple views, in order to correctly classify world information. This paper presents an active approach to solve this problem, with a tree-based (path)-planner which makes the vehicle executing a specific set of actions (following a specific trajectory), in order to discriminate among several possibilities. Results in simulation, with varying parameters, have shown that the algorithm is always bringing the robot to locations where it is expected that measurements would be different, according to the different environment.

PANDORA - Persistent Autonomy Through Learning, Adaptation, Observation and Replanning★

“…More detailed work discussing the need to consider uncertainty can be found in Maurelli et al [2013] and Maurelli et al [2014b]. A strategy to correctly label world information, linking the planning system to the classification module can be found in Maurelli et al [2014a].…”