Scalable sea floor imaging and monitoring

The project is developing scalable approaches to seafloor imaging using a team of simple underwater robots and robotic support surface vessels. This approach removes the bottleneck of current seafloor imaging practices making it cheaper and more accessible.

Schmidt Ocean Institute

Robotics and automation

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Duration

2 years

Academic team

Prof. Robert Fitch
Giovanni D’urso
James Ju Heon Lee
Ki Myung Brian Lee
Chanyeol Yoo
Australian Centre for Field Robotics
University of Rhode Island

Lab

Engagement model

Funding

Schmidt Ocean Institute

Future applications

Environmental monitoring
Underwater habitat mapping
Geological surveying
Improving oceanic environment data

Challenge

Seafloor imaging, surveying and monitoring is a critical component to maintaining a healthy marine ecosystem. Existing methods to survey vast oceanic environments require crewed vessels with experts that can deploy and operate imaging robots on multi-day or multi-week expeditions. Such an approach is expensive, both in terms of resources and human effort, and is a bottleneck for widespread accessibility for frequent benthic imaging.

Schmidt Ocean Institute is sponsoring research in techniques that remove this bottleneck by using a team of simple imaging robots called floats that can easily be deployed and operated by non-experts. Floats can control their depth, but otherwise drift along the ocean current. Ideally multiple floats are deployed from a support surface vessel such that they drift across regions of interest to image before being picked up, recharged, and redeployed. A robotic or crewed surface vessel schedule is needed to properly coordinate the float deploy and retrieval effort.

Solution

In collaboration with the Australian Centre for Field Robotics (ACFR) who were responsible for navigation, communication hardware design and construction, the UTS Tech Lab team developed the float deployment scheduler algorithm for a multi-vessel multi-float (MVMF) framework that maximise the number of points of interest observed. The University of Rhode Island has also participated, contributing terrain-aided navigation techniques to improve georeferencing of the floats.

The algorithm demonstrated, both in simulation and in real-world trials, that it’s suitable for practical applications. A robust scheduler allows benthic imaging to be either automated with minimal human intervention or performed by non-experts by providing a clear guideline on what order the floats should be dropped and picked up.

The resulting float-based benthic imaging framework offers a simple yet powerful tool for seafloor imaging. Removal of the bottleneck allows for frequent seafloor imaging to construct a more detailed ocean surveying, which is useful for ocean conservation (e.g., inspecting the health of coral reefs), marine robotics (e.g., reducing uncertainty of the environment), and geological surveying. Furthermore, the widespread accessibility this framework offers helps promote marine science and robotics to under-served communities; from enthusiast to developing countries. This promotion will also have a positive impact on constructing more detailed ocean surveying.

Seafloor imaging from floats