Vehicle Persistence Group

Mathieu Kemp, Principal Investigator

The goal of the Vehicle Persistence Group is to increase vehicle persistence. Persistence combines two elements, energy and reliability, one of which is the bottleneck. For most ocean-going systems, reliability is the limiting factor—mean-time-between failure of order 10 hours are not uncommon in autonomous underwater vehicles (AUV). As the user community continues to increase its reliance on AUVs, we are reaching a point where the technology is not keeping pace with the community’s needs. Our particular approach is to let the vehicle learn its own state-of-health (SOH) representations directly from its data, and to allow it to predict system failure before it happens.


LRAUV Testbed

Updates

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January 2017

Our new project, Fault Prognostication (see below) is just underway. We're in the process of adding a bunch of monitoring equipment to a benchtop version of the LRAUV (hyperlink to LRAUV pages) that we'll feed to unsupervised learning algorithms in order to learn the internal representation. Our initial focus is the vehicle's pitch pack, and to study it we're writing a LabView interface that will collect time-resolved data from a pair of vibration sensors + power usage + absolute position measurement.
Previous updates

Vehicle Persistence Projects

persistence observation

Fault Prognostication

Fault Prognostication is a 2017 new start funded by MBARI. The 3-year project will examine ways of improving persistence by improving the vehicle's fault diagnostic abilities and by implementing ways of prognosticating system failure before it happens.

Team

Technology

Solving challenges
Taking the laboratory into the ocean
In Situ Ultraviolet Spectrophotometer
Midwater Respirometer System
Mobile flow cytometer
Enabling targeted sampling
Automated Video Event Detection
Gulper autonomous underwater vehicle
Advancing a persistent presence
Aerostat hotspot
Benthic event detectors
Benthic rover
Fault Prognostication
Long-range autonomous underwater vehicle Tethys
Marine “soundscape” for passive acoustic monitoring
Monterey Ocean-Bottom Broadband Seismometer
Shark Café camera
Vehicle Persistence
Wave Glider-based communications hotspot
Emerging and current tools
Communications
Aerostat hotspot
Wave Glider-based communications hotspot
Data management
Oceanographic Decision Support System
Spatial Temporal Oceanographic Query System (STOQS) Data
Video Annotation and Reference System
Instruments
Apex profiling floats
Benthic event detectors
Deep particle image velocimetry
Environmental Sample Processor
How the ESP Works
Genomic sensors
ESP Web Portal
The ESP in the news
Investigations of imaging for midwater autonomous platforms
Lagrangian sediment traps
Laser Raman Spectroscopy
Midwater Respirometer System
Mobile flow cytometer
Smart underwater connector
Power
Wave-Power Buoy
Vehicle technology
Benthic Rover
Gulper autonomous underwater vehicle
Imaging autonomous underwater vehicle
In Situ Ultraviolet Spectrophotometer
Seafloor mapping AUV
Long-range autonomous underwater vehicle Tethys
Mini remotely operated vehicle
ROV Doc Ricketts
ROV Ventana
Video
Automated Video Event Detection
Deep learning
SeeStar Imaging System
Shark Café camera
Video Annotation and Reference System
Technology publications
Technology transfer

Recent Publications

Raanan, B.Y., Bellingham, J., Zhang, Y., Kemp, M., Kieft, B. Singh, H., Girdhar, Y., Automatic fault diagnosis for autonomous underwater vehicles using online topic models, published in IEEE Oceans 2016 Conference proceedings.

Raanan, B.Y., Bellingham, J., Zhang, Y., Kemp, M., Kieft, B. Singh, H., Girdhar, Y., Detection of unanticipated faults for autonomous underwater vehicle using online topic models, submitted to Journal of Field Robotics special issue on ocean robotics.