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Overview of Activities at the Australian Research Centre for Aerospace Automation (ARCAA), Queensland University of Technology. Troy Bruggemann A/Prof Rod Walker. Outline. ARCAA Background Current Research Research Samples (Vision and GNSS). What is ARCAA?. - PowerPoint PPT Presentation
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Overview of Activities at the Australian Research Centre for
Aerospace Automation (ARCAA), Queensland University of
Technology Troy BruggemannA/Prof Rod Walker
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Outline
• ARCAA Background
• Current Research
• Research Samples (Vision and GNSS)
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What is ARCAA?• A successful QLD Government Smart State
Research Facility Fund bid ($4M +)• Joint venture: CSIRO ICT Centre and QUT
Airborne Avionics Research group • Wide-spread support of industry and
government (DSTO, DITR, BAL, Boeing PW, SMEs)
• Initial focus on Civil Unmanned Air Vehicle (UAV) research for high-autonomy applications
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Research• Research to remove impediments facing the
routine use of UAVs for civilian applications– Focus on safety (vision, GNSS)– Reliability – Certification by regulators– Reduced operator requirements– Robustness (GNSS)– Reduced cost (increased automation)– Public acceptance (societal issues)
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ARCAA Facilities
• A dedicated research, development and commercialisation facility
• Space for ~40 researchers, developers
• World class simulation and testing facilities to be developed
• Fostering international collaboration
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Who we are?
• CRC for Satellite Systems• 18 PhD students in 2006• 30 undergraduate
Avionics students/year• 5 full-time CSIRO staff• 8 full-time QUT staff
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ARCAA Workshop• Major Sponsor
IEEE AESS• 100+
delegates• Workshop to
drive ARCAA research programs
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ARCAA Workshop
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NWorkshop OutcomesWorkshop Outcomes
Flight Systems & Safety
– Reliable low cost systems (GNSS)
– Safety of Autonomous Aircraft• ‘Virtual safety bubble’• See-N-Avoid • Advanced FTS (Forced
Landing)– Future air traffic management
technologies (pFMS)– Increased onboard autonomy – Intuitive Operator interfaces
(Drag-N-Fly)
OPPORTUNITIES
Civ. Applications
– Infrastructure• Powerlines• Pipelines• Buildings• Towers / Bridges
– Environmental• Bushfires• Farms / Land• Rivers / Reef
– Search and support– Surveillance
Political, Social & Regulatory
– Insurance
– Regulations – next generation ‘101’
– UAV Risk management
– Certification standards and industry ‘best practice framework
– Community acceptance
– UAV training
KEY IMPEDIMENTS
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Current QUT Research Areas• advanced collision avoidance systems • intelligent mission planning • flight termination systems • vision-based navigation and GNSS attitude
determination systems • onboard flight performance analysis and adaptive
control • investigation into UAV risk identification and certification • airborne Ground-based Regional Augmentation System
(GRAS) receiver
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QUT Research Sampler #1• Vision-Based method of
estimating Pitch and Roll• Real-Time implementation
on standard computers• Developed for wide range
of cameras• Provides a level of virtual
redundancy
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QUT Research Sampler #2
• UAV Collision Avoidance– Current FAA regulations require UAVs to be
provided with…
“a method that provides an equivalent level of safety, comparable to the see-and-avoid requirements of manned aircraft”
[U.S. FAA Order 7106.4 Chapter 12, Section 9]
– Can computer vision be used to provide a reliable, cost-effective see and avoid capability?
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QUT Research Sampler #2
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QUT Research Sampler #2
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QUT Research Sampler #3• UAV Forced Landing
Research• Human pilots trained for
forced landings– Detect and evaluate slope,
surface, shape, field surroundings, proximity to emergency services
• Why not UAVs?
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QUT Research Sampler #4
• GRAS Airborne Navigation Receiver Augmentation using Low CostMEMS Inertial Sensors and aerodynamic modelling for General Aviation Aircraft
• This research is funded by the ARC, Airservices Australia and GPSat Systems Australia.
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QUT Research Sampler #4
• Require Signal-in-Space of GRAS and GPS– Coverage limited by line-of-sight and modulation
scheme– What areas are out of coverage at altitudes where
GA are operating?
• Cannot account for local effects – Un-modelled atmospheric effects (eg. scintillation)– Multi-path, receiver errors, equipment failures
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QUT Research Sampler #4
• Development of a framework and architecture for high integrity navigation for G.A aircraft using– GRAS technology– MEMS technology
• Evaluate the benefits and remaining challenges of using low-cost MEMS inertial devices for approach navigation in G.A.
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QUT Research Sampler #4
• Research new strategies for aerodynamic modelling to improve GPS integrity monitoring for general aviation
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QUT Research Sampler #5• Single Antenna GPS
Attitude Algorithm for non-uniform Antenna Gain Pattern
• New algorithm RMS error = 13.8 deg.
Previous algorithms:• Duncan rms error =
21.5 deg
• Axelrad rms error = 16.4 deg
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QUT Research Sampler #6
• Fixed Wing UAV Navigation and Control through IntegratedGNSS and Vision(GVSS)
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QUT Research Sampler #6• Optic Flow
Method
• Image flow generated from image stream– Gradient based
method being utilised
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QUT Research Sampler #6• Optic Flow Method
– Looking at characteristics of gradient based optic flow and the possibility of utilizing other methods
– Feature tracking approach for sparse velocity measurements
Sensor Architecture
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Abnormal Flight - StallResults
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GVSS Controlled Flight
Mean [deg] Std. [deg]
Roll -0.25 0.9388
Pitch
-0.1465 0.1898
Yaw 0.1651 0.3178
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QUT Research Sampler #6• The GVSS shows potential in the confines
of the simulation environment– Sub-degree Euler angle accuracy– Capable of being used to drive the control
loop– Flight path information– Flight control information– Collision avoidance information
Conclusion
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QUT Research Sampler #6• Tightly Coupled GNSS / Vision
Information for Improved Fault Tolerant UAV Flight Control
• GNSS / Vision using Multiple Image Sources
Conclusion