Saildrone Surveyor: Autonomous Mapping and Environmental Characterization

PI: Mayer, Larry (University of New Hampshire)
Co-PI(s): Scholin, Christopher (Monterey Bay Aquarium Research Institute) : Birch, James (Monterey Bay Aquarium Research Institute) : Jenkins, Richard (Saildrone Inc.) : Calder, Brian (University of New Hampshire)
Start Year: 2019 | Duration: 3 years
Partners: University of New Hampshire, Monterey Bay Aquarium Research Institute, Saildrone Inc.

Project Abstract:

The University of New Hampshire (UNH), Saildrone, and the Monterey Bay Aquarium Research Institute (MBARI) propose a three-year demonstration project with the overall objective of developing an unmanned wind-powered system capable of long-duration missions (6-12 months) that can map the seafloor, water column and critical environmental variables, transmit data to shore in real-time, and offer the opportunity for adaptive mission planning and control in response to targets of interest. When fully scaled, such an approach offers a very cost-effective means for the collection of mapping, water column and environmental data for the entire exclusive economic zone and addressing several NOAA long-term mission goals including “healthy oceans” and “resilient coastal communities and economies.” The effort will be focused around the new 72-foot Saildrone Surveyor autonomous surface vehicle that is currently under development and will initially deploy in the spring of 2019. Leveraging its investment in the development of this uniquely capable platform, Saildrone will build upon its successful record (more than 500,000 nautical miles already logged) of deployment and data collection from their 23-foot standard Saildrones, and integrate a complete suite of environmental sensors on the Saildrone Surveyor including a CO2 sensor, and a biogeochemistry suite (Chl-a, CDOM, Red backscatter, dissolved pCO2, atmospheric pCO2, DO, pH). Working with UNH and Kongsberg, Saildrone will install three state-of-the-art sonar systems (EM304 deep water multibeam, EM2040 shallow water multibeam, and EK-80 scientific echo sounder) allowing detailed mapping of the seafloor (bathymetry and backscatter) and the water column. Sound speed will be monitored by expendable bathythermographs or a small autonomous winch-based system currently being developed by Saildrone in cooperation with NOAA. Working with MBARI, Saildrone will integrate its third generation Environmental Sample Processor (3G ESP) sampler that is designed to support studies of harmful algal blooms, microbial ecology, water quality monitoring, and to collect environmental DNA indicative of invasive species and larger animals. The 3G ESP uses self-contained “cartridges,” each of which carries their own sample collection media and reagents for sample preservation. Sixty of these cartridges are arranged in a rotatable ring around a central axis.

Command and Control and data communication with the Saildrone is through Iridium short-burst data, duplicated for redundancy. System health data is sent back via duplicated Iridium Rudics Modems. Data from the sonar and other data systems are transmitted via dual KVH V7HTS units which currently offer 10 Mbps down and 3 Mbps up. There will be one KVH unit each side of the wing to ensure good sky visibility at all angles of sail. The Saildrone Surveyor will be piloted remotely rather than operated fully autonomously. In this mode, domain awareness data (GPS, visual cameras, radar, AIS and metocean sensors) will be relayed in real time to a shore-based operator via broadband satellite communication. The operators will pilot the Saildrone Surveyor on a watch schedule that will ensure 24/7 human-in-the-loop decision making, similar to how heavy-duty unmanned aerial vehicles are managed today. This mode of operation will also allow adaptive mission planning and sampling whenever sensors indicate an area of interest.

The project partners will conduct two Saildrone Surveyor data collection missions each year for three years; initial missions will take place off California and in an uncrewed transit from San Francisco to Hawaii. Each data mission will have a minimum five-day duration each year, with yearly iterations allowing for continued improvement and significantly increased technical readiness. UNH will analyze and evaluate data quality in order to provide feedback and direction to ensure the technology is capable of full U.S. exclusive economic zone mapping. It will also lead the development of autonomous data quality monitoring tools as well as tools to identify targets of interest.

BAA: N00014-18-S-B007
BAA Topic: Autonomous mapping