2011 National Air Quality Conferences - PowerPoint Presentation

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2011 National Air Quality ConferencesJ.B. Kosmatka, Project LeadThomas S. Hong, Student Lead (Presenter)Department of Mechanical and Aerospace EngineeringUniversity of California, San DiegoMassimiliano Lega, CollaboratorDipartimento di Scienze per l’Ambiente, Universita degli Studi di Napoli PartenopeGiuseppe Persechino, CollaboratorCIRA, Italian Aerospace Research CentreMarch 9th, 2011

Air Quality Plume Characterization and Tracking using small unmanned aircraft

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OutlineIntroductionPlumesUASCurrent SystemCapabilitiesProposed Test DetailsThe FutureComposite Aerospace Structures Laboratory

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Introduction: PlumesA volume of gas or fluid with a composition of interest moving through anotherComposite Aerospace Structures LaboratoryMt. Etna (NASA Image)

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Introduction: PlumesMake up can be particulate, chemical, biological, radioactive matter Composite Aerospace Structures LaboratoryEscondido Controlled Burn (AP Photo)

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2007 California Wildfires (NASA Image)Introduction: PlumesWind shear causes plume drift that is hard to predictVarying scale plumes call for a scalable solutionPotentially invisible and or hazardous to life and manned sensorsComposite Aerospace Structures Laboratory

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Introduction: Unmanned Aerial SystemUsed in 3-D missionsDull, Dirty or DangerousSmall Unmanned Aerial System (sUAS)More maneuverable than full sized counterpartsLower operational costsCan be launched and recovered almost anywhereComposite Aerospace Structures LaboratoryRaven UAS (Aerovironment photo)

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Small electric airframe with pusher propeller2 lbs maximum weightEndurance with payload: 30 minutesComposite Aerospace Structures LaboratoryMultiplex Easy Star 54”(UCSD photo)System Details: aircraft

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Kestrel 2.2 COTS autopilot – GPS, IMU, multiple failsafesAllows for a easily controlled and fully autonomous aircraftA external multiplexor is used so that the safety pilot can take over the aircraft at any timeComposite Aerospace Structures LaboratoryKestrel 2.X (Procerus Technologies photo)

System Details: Autopilot

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SHARP Compact Optical Dust Sensor Saturated by visible smoke Allows us to map the boundaries of test plumesComposite Aerospace Structures LaboratoryOptical dust sensor(SHARP photo)System Details: Smoke sensor

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System Details: Prior ArtKemp et al. 2004Bang-Bang algorithm with multiple UUVsCoordination achieved bychanging speed of UUVsComposite Aerospace Structures LaboratoryComplete vs. incomplete coverageCoverage of three perimeters

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System Details: Prior ArtHsieh et al. 2005Implementation of the Kemp method on ground robots (2D experiment)Were satisfied with results and its ease of implementationComposite Aerospace Structures LaboratoryGround tracks of three robots and cooperatively gathered boundary points

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System Details: Prior ArtEncountered a problem:Fast moving vehicles with limited maneuverabilityLimited plume sizesComposite Aerospace Structures Laboratory

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System DetailsPlume boundary mapping and tracking via fly-through and centroid measurementsComposite Aerospace Structures LaboratoryMATLab simulation(UCSD image)

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System DetailsComposite Aerospace Structures LaboratoryMATLab simulation(UCSD image)

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System DetailsComposite Aerospace Structures LaboratoryMATLab simulation(UCSD image)

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System DetailsAllows for initial 2-D mapping, and tracking of plume by individual UAVs for a 3-D composite imageComposite Aerospace Structures Laboratory

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The controls group has conducted a autonomous ground test with multiple ground robotsControl of the robots as well as their data were handled by an off-site super computerComposite Aerospace Structures LaboratoryGround robot testing(UCSD photo)Previous Testing

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2009 testing was conducted at Los Alamos, New MexicoPlume characterization tests were conducted without aircraft, and once characterized, the UAVs were flown through the plume for sensor dataComposite Aerospace Structures LaboratorySmoke testing at Los Alamos (UCSD photos)Previous Testing

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Learned that smaller and slower aircraft were neededComposite Aerospace Structures LaboratoryFlight test data (UCSD image)Previous Testing

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Cooperative flight (UCSD photo)Coordinated flight with 3 UAVs at different altitudesComposite Aerospace Structures LaboratoryPrevious Testing

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Gridded initial search pattern highlights grids with positive readings Highlighted grids can be meshed finer then re-queried Human operator can pick grids of interest if there are multiple regionsComposite Aerospace Structures LaboratoryGridded search simulation(UCSD image)

Previous Testing

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Once a positive detection is made, the algorithm goes into tracking modeTracking algorithm simulation (UCSD image)Composite Aerospace Structures LaboratoryPrevious Testing

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Simulated smoke missions at UCSD (UCSD photo)Servo operated plunger simulated smokeSuccessful tracking and estimation of plume boundariesComposite Aerospace Structures LaboratoryPrevious Testing

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Flight tests to be conducted at NASA DrydenFAA regulated flights with multiple UAVsAircraft will autonomously track released smoke using the boundary mapping algorithms and wind estimationsComposite Aerospace Structures LaboratoryFuture Tests2011 Flight Testing Schedule: May: Good, Low winds (5-10 days possible) June: Good, Low winds (10-15 days possible) July: Great, no wind, hot (30 days possible, dawn flight) August: Great, no wind, hot (30 days possible, dawn flight) September: Great, no wind, hot (30 days possible, dawn flight)

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Cruise Ship Pollution and Marine Shipping off of Anacapa Island, CA (Jim Walker, APCD photo)Composite Aerospace Structures LaboratoryFuture Tests

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Major shipping routes (CruiseLawNews image)Composite Aerospace Structures LaboratoryFuture Tests

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Questions?AknowledgementsChad Foerster, Nima Ghods, Tim Wheeler, David Zhang, 1Charles Farrar, Will Fox, Matthew Bement, Mike Proicou, and Jeffery Hill 21 University of California, San Diego2 Los Alamos National LabComposite Aerospace Structures Laboratory