Autonomous Adaptive Underwater Exploration using Online Topic Modeling

Abstract

Exploration of underwater environments, such as coral reefs and ship wrecks, is a difficult and potentially dangerous tasks for humans, which naturally makes the use of an autonomous robotic system very appealing. This paper presents such an autonomous system, and shows its use in a series of experiments to collect image data in an underwater marine environment.We presents novel contributions on three fronts. First, we present an online topic-modeling based technique to describe what is being observed using a low dimensional semantic descriptor.KeywordsVisual WordLatent Dirichlet AllocationForward VelocityTopic DistributionProbabilistic Latent Semantic AnalysisThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.