Title: Localization and Active Exploration in Indoor Underwater Environments

Abstract:

Autonomous underwater vehicles have the potential to inspect and map indoor underwater environments, such as spent nuclear fuel pools and ship ballast tanks. Towards this, the thesis makes contributions in the domains of visual localization and active SLAM for underwater environments. In the first work, we propose a novel through-water method for visual localization using landmarks above the water surface. Using ideas from multimedia photogrammetry in our localization framework, we model refraction at the water-air interface. We evaluate our method via both simulation and real-world experiments in a test-tank environment. The second work presents an active SLAM approach for sonar mapping of these environments. Building on previous work in mapping and planning, we devise an exploration policy that bounds pose uncertainty through revisit actions. A revisit policy is selected based on submap saliency, propagated pose uncertainty and path information gain. We demonstrate the system in simulation and highlight the advantages over an uncertainty-agnostic framework.

Committee:
Michael Kaess (advisor)

David Wettergreen

Maxim Likhachev

Eugene Fang