The PIs have requested a Gulf oil spill RAPID award to construct, validate, and deploy within selected Gulf and coastal waters, an operational adaptive mobile robotic sampler platform for in-water capture and return of oil spill chemical, microbial and particulate matter. The system is comprised of a robotic sampling payload coupled with a renewable energy (solar) autonomous underwater vehicle (SAUV), both were technologies supported by past NSF funding. The project will demonstrate a basic technological capability integrating a mobile underwater platform (robot) with sensing and robotic sampling instrumentation in order to support the automated study of biological and chemical phenomena through spatio-temporal data acquisition and model-based sampling. The prototype sensor/sampling/platform system will support an adaptive approach to physical sampling of the Deep Water Horizon Oil Spill impact zone. The system implementation addresses fundamental issues in intelligent aquatic based platforms and control of complex interactive systems. The mobile sampler system will advance the temporal and spatial sampling of the oil and other contaminants which may have fundamental impacts on the less-visible portions of the delicate chemical and biological ecosystem of the Gulf of Mexico.
Broader Impacts
In the near term, this program addresses a unique window of opportunity to provide spatial and temporal mapping of the Gulf oil spill and its impact on ecosystem viability. The mobile sampling and adaptive sampling principles will apply to many other domains where such complex sampling based networks can be utilized. The adaptive chemical sampling approach will impact ocean technology and ocean science with a new sampling modality. Sampling of remote ocean material coupled to standard lab based analysis can permit investigations toward high priority science questions related to complex ecosystems. The influence of this work could spill over into all areas of oceanography (biological, chemical, physical, geological and coupled version of the four areas). The mobile sampling platform technology may be extended to study other marine phenomena including, for example, harmful algal blooms (HAB), fine structure of plankton distributions, and coastal contamination.
The expected impact of the project, if successful, will be in the systems engineering feat for a low cost adaptive intelligent aquatic sampling system. The work will produce an innovative and intelligent hardware framework capable of purifying and detecting bio/chemical targets in complex, natural samples. The physical system will be promoted as a prominent example of interdisciplinary design and technology education with the use of renewable energy, intelligent systems and robotics. Education and outreach efforts to general audiences will include remote access to the sampling operational activity and project results.
The project is a technology solution for a long duration and long range automated/mobile/adaptive screening and sampling system. The application of this innovation can be used for; establishing baseline, responding, monitoring, spatially mapping and controlling oil impacted ecosystems. This single technology can provide a range of adaptive and intelligent support for charactering indicator chemistry, microbiology and microparticulate matter of an ecosystem, before, during or after an oil spill. This automated mobile sampling system is comprised of three modules: 1) solar autonomous underwater vehicle embedded inside a MARCON kit enabled robotic surface vessel, 2) oil adaptive sensing module and 3) robotic fluidic sampler/archival unit. Specific outcomes included: -The construction, validation, and deployment within selected Gulf and coastal waters, of an operational mobile robotic sampler platform for the capture and return of oil spill chemical, microbial and particulate matter. -Created a novel sensor/robot machine that messaged, in written human language, the sensor data being collected while deployed in the water. - Exposure of this project to the general public for informal science education occurred through the novel "tweeting" messaging from the SAUV system while out at sea. Local, regional and national news coverage was achieved. - Created an oil adaptive sensing and sampling module that is based on a low cost Arduino electronic controller combined with a fast screening optical sensor that triggers the robotic sampler for specific verification of oil composition back in the lab. -Applied the mobile sampling system to other targets beyond oil including, harmful algal blooms, pesticides in water, toxins in water, and oil tracer compounds. -Generated the robotic tool kit (robotic mobile vehicles, robotic water sampler, and intelligent controllers) to be the basis for an undergraduate Field and Experiential Learning Course to be offered in 1Q 2013 at University of South Florida St Petersburg. -Created a completely automated process for sampling the ocean, to automated chemical and biological analysis in the lab, and for automated intelligent messaging from real time sensors on the mobile robot while out at sea. -Four publications have been completed, two on the mobile sampling system and two on the adaptive sampling techniques, and two additional publications are in process related to field exercises. - The design and construction of an automation kit designated MARCON (Mobile, Autonomous and Remotely Controlled Observation Node) for a cheaper more lightweight and open-source automation system for surface vehicles. - Creation and application of a visual data collection and mapping system to project obtained data to researchers and the public community.
