  Underwater ROVs (Remotely Operated Vehicles) are unmanned submersible
vehicles designed for exploring and operating in the depths of the ocean.
Despite using high-end cameras, typical teleoperation engines based on
first-person (egocentric) views limit a surface operator's ability to maneuver
the ROV in complex deep-water missions. In this paper, we present an
interactive teleoperation interface that enhances the operational capabilities
via increased situational awareness. This is accomplished by (i) offering
on-demand "third"-person (exocentric) visuals from past egocentric views, and
(ii) facilitating enhanced peripheral information with augmented ROV pose
information in real-time. We achieve this by integrating a 3D geometry-based
Ego-to-Exo view synthesis algorithm into a monocular SLAM system for accurate
trajectory estimation. The proposed closed-form solution only uses past
egocentric views from the ROV and a SLAM backbone for pose estimation, which
makes it portable to existing ROV platforms. Unlike data-driven solutions, it
is invariant to applications and waterbody-specific scenes. We validate the
geometric accuracy of the proposed framework through extensive experiments of
2-DOF indoor navigation and 6-DOF underwater cave exploration in challenging
low-light conditions. A subjective evaluation on 15 human teleoperators further
confirms the effectiveness of the integrated features for improved
teleoperation. We demonstrate the benefits of dynamic Ego-to-Exo view
generation and real-time pose rendering for remote ROV teleoperation by
following navigation guides such as cavelines inside underwater caves. This new
way of interactive ROV teleoperation opens up promising opportunities for
future research in subsea telerobotics.
