Abstract
This paper addresses visual navigation of autonomous underwater vehicles (AUVs) with and without a given map, where the latter is called Simultaneous Localization and Mapping (SLAM). We summarize the challenges and opportunities in underwater environments that make visual navigation different from land navigation and also briefly survey the current state-of-the-art in this area. Then as a position paper we argue why many of these challenges could be met by a proper modeling of uncertainties in the SLAM representation. This would in particular allow the SLAM algorithm to thoroughly handle the ambiguity between “I see the same feature again.”, “I see a different but similar looking feature.” and “The environment has changed and the feature moved.”.
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