Abstract:
As analysis of imagery and environmental data plays a greater role in mission construction
and execution, there is an increasing need for autonomous marine vehicles
to transmit this data to the surface. Without access to the data acquired by a
vehicle, surface operators cannot fully understand the state of the mission. Communicating
imagery and high-resolution sensor readings to surface observers remains
a significant challenge – as a result, current telemetry from free-roaming
autonomous marine vehicles remains limited to ‘heartbeat’ status messages, with
minimal scientific data available until after recovery. Increasing the challenge, longdistance
communication may require relaying data across multiple acoustic hops
between vehicles, yet fixed infrastructure is not always appropriate or possible.
In this thesis I present an analysis of the unique considerations facing telemetry
systems for free-roaming Autonomous Underwater Vehicles (AUVs) used in exploration.
These considerations include high-cost vehicle nodes with persistent storage
and significant computation capabilities, combined with human surface operators
monitoring each node. I then propose mechanisms for interactive, progressive
communication of data across multiple acoustic hops. These mechanisms include
wavelet-based embedded coding methods, and a novel image compression scheme
based on texture classification and synthesis. The specific characteristics of underwater
communication channels, including high latency, intermittent communication,
the lack of instantaneous end-to-end connectivity, and a broadcast medium,
inform these proposals. Human feedback is incorporated by allowing operators to
identify segments of data thatwarrant higher quality refinement, ensuring efficient
use of limited throughput. I then analyze the performance of these mechanisms
relative to current practices.
Finally, I present CAPTURE, a telemetry architecture that builds on this analysis.
CAPTURE draws on advances in compression and delay tolerant networking to
enable progressive transmission of scientific data, including imagery, across multiple acoustic hops. In concert with a physical layer, CAPTURE provides an endto-
end networking solution for communicating science data from autonomous marine
vehicles. Automatically selected imagery, sonar, and time-series sensor data
are progressively transmitted across multiple hops to surface operators. Human
operators can request arbitrarily high-quality refinement of any resource, up to an
error-free reconstruction. The components of this system are then demonstrated
through three field trials in diverse environments on SeaBED, OceanServer and
Bluefin AUVs, each in different software architectures.
