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FRoSt Lab
Field Robotic Systems Lab

Research

The Field Robotic Systems Lab (FRoSt Lab) at Brigham Young University is focused on enabling the development of robust and reliable field-robotic systems that are able to consistently perceive, navigate, and perform work in complex unstructured real-world environments.

Current Research

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HoloOcean Underwater Simulator

Built on Unreal Engine 4, our simulator accurately models sonar, buoyancy, acoustic communications and more. Learn more here.
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Active Data Collection

We are developing novel semi-supervised machine learning algorithms that will allow AUVs to more efficiently plan their own paths based on actively inferred environmental patterns in combination with pre-embedded scientific knowledge.
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Reef Mapping / Characterization

Autonomous surveying/mapping for investigating the preservation of coral reefs in Samoa and Hawaii
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Cross Modality

Improving information exchange and interaction between sensors in both single and multi-agent systems
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Autonomous Civil Infrastructure Inspection

The FRoSt Lab is developing methods to enable autonomous underwater vehicles to automatically inspect underwater structures such as ship hulls, dams, bridges, and piers.
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Long-Term Coastal Semantic Localization

Comparing current observations of coastline environments to previously made predictions in order to achieve localization with respect to semantically labeled maps that may be outdated, expanding the possibilities of coastal monitoring in GPS-denied situations.
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Navy Engineering Education Consortium (NEEC)

Building simple and cheap UUV vehicles used for cooperative robotic applications
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Past Research

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Automatic Fault Diagnosis/Repair

Autonomous fault detection and repair on self driving vehicles
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Efficient Hardware Implementations or Robotics Algorithms via HLS

Improving the efficiency of robotics perception, estimation, and planning algorithms through the use of High-Level Synthesis (HLS) to generate custom FPGA circuitry.
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Autonomous Wheelchair Navigation

By leveraging techniques from autonomous driving, we are developing an autonomous all-terrain stairclimbing wheelchair that can enable those with limited control to experience the outdoors and travel to locations not previously accessible to them.
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Multi-agent Communication-constrained Underwater Mapping

Enabling multiple underwater vehicles to collaboratively map or search environments while taking into account the strict communication constraints inherent to the underwater domain.
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