2011 national air quality conferences j.b. kosmatka , project lead
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Air Quality Plume Characterization and Tracking using small unmanned aircraft. 2011 National Air Quality Conferences J.B. Kosmatka , Project Lead Thomas S. Hong, Student Lead (Presenter) Department of Mechanical and Aerospace Engineering University of California, San Diego - PowerPoint PPT PresentationTRANSCRIPT
2011 National Air Quality Conferences
J.B. Kosmatka, Project LeadThomas S. Hong, Student Lead (Presenter)Department of Mechanical and Aerospace EngineeringUniversity of California, San Diego
Massimiliano Lega, CollaboratorDipartimento di Scienze per l’Ambiente, Universita degli Studi di Napoli PartenopeGiuseppe Persechino, CollaboratorCIRA, Italian Aerospace Research Centre
March 9th, 2011
AIR QUALITY PLUME CHARACTERIZATION AND TRACKING USING SMALL UNMANNED AIRCRAFT
OUTLINE Introduction
Plumes UAS
Current System Capabilities
Proposed Test Details
The Future
Composite Aerospace Structures Laboratory
INTRODUCTION: PLUMES
A volume of gas or fluid with a composition of interest moving through another
Composite Aerospace Structures Laboratory
Mt. Etna (NASA Image)
INTRODUCTION: PLUMES
Make up can be particulate, chemical, biological, radioactive matter
Composite Aerospace Structures Laboratory
Escondido Controlled Burn (AP Photo)
2007 California Wildfires (NASA Image)
INTRODUCTION: PLUMES Wind shear causes
plume drift that is hard to predict
Varying scale plumes call for a scalable solution
Potentially invisible and or hazardous to life and manned sensors
Composite Aerospace Structures Laboratory
INTRODUCTION: UNMANNED AERIAL SYSTEM
Used in 3-D missions Dull, Dirty or
Dangerous Small Unmanned Aerial
System (sUAS) More maneuverable than
full sized counterparts Lower operational costs Can be launched and
recovered almost anywhere
Composite Aerospace Structures Laboratory
Raven UAS (Aerovironment photo)
Small electric airframe with pusher propeller
2 lbs maximum weight Endurance with payload: 30 minutes
Composite Aerospace Structures Laboratory
Multiplex Easy Star 54”(UCSD photo)
SYSTEM DETAILS: AIRCRAFT
Kestrel 2.2 COTS autopilot – GPS, IMU, multiple failsafes
Allows for a easily controlled and fully autonomous aircraft
A external multiplexor is used so that the safety pilot can take over the aircraft at any time
Composite Aerospace Structures Laboratory
Kestrel 2.X (Procerus Technologies photo)
SYSTEM DETAILS: AUTOPILOT
SHARP Compact Optical Dust Sensor
Saturated by visible smoke
Allows us to map the boundaries of test plumes
Composite Aerospace Structures Laboratory
Optical dust sensor(SHARP photo)
SYSTEM DETAILS: SMOKE SENSOR
SYSTEM DETAILS: PRIOR ART
Kemp et al. 2004 Bang-Bang algorithm
with multiple UUVs Coordination achieved by
changing speed of UUVs
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Complete vs. incomplete coverage
Coverage of three perimeters
SYSTEM DETAILS: PRIOR ART
Hsieh et al. 2005 Implementation of the Kemp
method on ground robots (2D experiment)
Were satisfied with results and its ease of implementation
Composite Aerospace Structures Laboratory
Ground tracks of three robots and cooperatively gathered boundary points
SYSTEM DETAILS: PRIOR ART
Encountered a problem: Fast moving vehicles with limited
maneuverability Limited plume sizes
Composite Aerospace Structures Laboratory
SYSTEM DETAILS
Plume boundary mapping and tracking via fly-through and centroid
measurements
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MATLab simulation(UCSD image)-150 -100 -50 0 50 100
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Centroid Tracking Algorithm
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SYSTEM DETAILS
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MATLab simulation(UCSD image)
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Centroid Tracking Algorithm
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SYSTEM DETAILS
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MATLab simulation(UCSD image)
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Tracking Algorithm with Moving Plume
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SYSTEM DETAILS
Allows for initial 2-D mapping, and tracking of plume by individual UAVs
for a 3-D composite imageComposite Aerospace Structures Laboratory
The controls group has conducted a autonomous ground test with multiple ground robots
Control of the robots as well as their data were handled by an off-site super computer
Composite Aerospace Structures Laboratory
Ground robot testing(UCSD photo)
PREVIOUS TESTING
2009 testing was conducted at Los Alamos, New Mexico
Plume characterization tests were conducted without aircraft, and once characterized, the UAVs were flown through the plume for sensor data
Composite Aerospace Structures Laboratory
Smoke testing at Los Alamos (UCSD photos)
PREVIOUS TESTING
Learned that smaller and slower aircraft were needed
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Flight test data (UCSD image)
PREVIOUS TESTING
Cooperative flight (UCSD photo)
Coordinated flight with 3 UAVs at different altitudes
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PREVIOUS TESTING
• 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 regions
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Gridded search simulation(UCSD image)PREVIOUS TESTING
Once a positive detection is made, the algorithm goes into tracking mode
Tracking algorithm simulation (UCSD image)
Composite Aerospace Structures Laboratory
PREVIOUS TESTING
Simulated smoke missions at UCSD (UCSD photo)
Servo operated plunger simulated smoke Successful tracking and estimation of plume
boundaries
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PREVIOUS TESTING
Flight tests to be conducted at NASA Dryden FAA regulated flights with multiple UAVs Aircraft will autonomously track released smoke using
the boundary mapping algorithms and wind estimations
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FUTURE TESTS
2011 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)
Cruise Ship Pollution and Marine Shipping off of Anacapa Island, CA (Jim Walker, APCD photo)
Composite Aerospace Structures Laboratory
FUTURE TESTS
Major shipping routes (CruiseLawNews image)
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FUTURE TESTS
QUESTIONS?Aknowledgements
Chad Foerster, Nima Ghods, Tim Wheeler, David Zhang, 1
Charles Farrar, Will Fox, Matthew Bement, Mike Proicou, and Jeffery Hill 2
1 University of California, San Diego2 Los Alamos National Lab
Composite Aerospace Structures Laboratory