utat uav pdr 2015.pptx
TRANSCRIPT
University of Toronto Aerospace TeamUAV [email protected]
DateLocationSpeakers
University of Toronto Aerospace TeamUAV [email protected]
Preliminary Design Review
University of Toronto Aerospace TeamUAV Division
November 21, 2015BA3116UAV Division
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University of Toronto Aerospace TeamUAV [email protected]
Agenda• Competition Overview• System Level Design• Payload• Computer Vision• Communications• Airframe• Fabrication• Mechanical• Avionics• Ground Control Station• Systems Testing and Risk Analysis
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~12.30-13.00 Lunch Break
University of Toronto Aerospace TeamUAV [email protected]
University of Toronto Aerospace TeamUAV [email protected]
COMPETITIONS OVERVIEW
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University of Toronto Aerospace TeamUAV [email protected]
Unmanned Systems Canada 2016
UAV agricultural application:• Estimate crop surface
area• Determine crop geo-
location• Read QR code inside
each crop area• Detect 940 nm IR
Target• Deploy (3) probes into
designated crop areas4
University of Toronto Aerospace TeamUAV [email protected]
AUVSI SUAS 2016
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UAV primary mission tasks: • Fully autonomous UAV
operation• Telemetry
interoperability with competition server
• Determine alphanumeric target characteristics and geo-location
• Read QR Code• Secondary: ADLC,
Actionable Intelligence, Emergent Task, Air-Drop
University of Toronto Aerospace TeamUAV [email protected]
UAV Challenge Medical Express
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UAV blood sample return: • Fly 20-30 km from
base to remote landing site
• Estimate dummy geo-location at remote landing site
• Land 30 – 80 m from dummy
• Retrieve the blood sample and return to base
University of Toronto Aerospace TeamUAV [email protected]
MedEx Justification
• Well proven USC/AUVSI airframe that meets performance specifications of these competition– Requires no major airframe design
modifications• No PWF SAE AeroDesign competition
– No other aircraft design within UTAT• No registration fee• Veteran members
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University of Toronto Aerospace TeamUAV [email protected]
USC/AUVSI Schedule
PDRNov 21
Detailed DesignNov - Dec
USC Repo
rtJan 15 USC Full
Sys TestingMar - Apr
USC FlightApr 27 – May 1
AUVSI Full Sys TestingMay - Jun
AUVSI ReportMay 18
AUVSI Flight Jun
15 – 18
System Integrati
onJan - Feb
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University of Toronto Aerospace TeamUAV [email protected]
Medical Express Schedule
PDRNov 21
Detailed Design
Nov - Dec
Retrieval A/C
TestingMar - Apr
MedEx D2 Flight Proof
Apr 13
Full Systems TestingAug - Sep
MedEx D3Aug 10
MedEx Flight Sep
27 – 30
System Integrati
onJan - Mar Full
Systems TestingApr - Aug
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University of Toronto Aerospace TeamUAV [email protected]
University of Toronto Aerospace TeamUAV [email protected]
SYSTEM ENGINEERINGLead: Oliver Wu (ECE 1T7)
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University of Toronto Aerospace TeamUAV [email protected]
University of Toronto Aerospace TeamUAV [email protected]
MEDICAL EXPRESSFUNCTIONAL FLOW BLOCK DIAGRAM
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
University of Toronto Aerospace TeamUAV [email protected]
MEDICAL EXPRESSBLOCK DIAGRAM
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University of Toronto Aerospace TeamUAV [email protected]
MedEx Configuration Justification• Long distance >10KM• No LOS• Constant telemetry required• Unpredictable landing site (VTOL
only)
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
University of Toronto Aerospace TeamUAV [email protected]
USC AND AUVSI BLOCK DIAGRAM
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
University of Toronto Aerospace TeamUAV [email protected]
PAYLOAD SUBSYSTEMWINSTON LIU
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University of Toronto Aerospace TeamUAV [email protected]
Unmanned Systems Canada (April 29th - May 1st)
• Calculate crop areas - delineated on corners by 40-inch colored ribbons, and give GPS coordinates of centroid
• Read QR codes located within crop area• No points for automatic detection• Processing time = 1 hour post-flight
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Competition Requirements-USC
University of Toronto Aerospace TeamUAV [email protected]
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Competition Requirements-AUVSI (1)
AUVSI (June 15th - 19th)Primary task: localize and classify targets
and QR codesSecondary tasks:
– ADLC: classify 3 characteristics autonomously; decode QR code; 67% classification rate. 6 targets will be scored.
– Actionable Intelligence: perform ADLC on 1 target while airborne
– Off-axis target: capture and characterize– Emergent target: in-flight re-tasking– Air-drop: take pictures of the target
University of Toronto Aerospace TeamUAV [email protected]
• Characterize targets:1. Location (lat, lon)2. Letter orientation (N, NE, E, SE, S, SW, W,
NW)3. Shape, 13 possibilities4. Alphanumeric character5. Color of character6. Color of shape
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Competition Requirements-AUVSI (2)
University of Toronto Aerospace TeamUAV [email protected]
Medical Express (Sep 19th-22nd)• Locate Outback Joe in 1 km diameter circle• Find landing spot, and land. Requires VTOL• Using two aircraft, 1 to relay, 1 to land• Recent rules update stated grass runways are
available for takeoff• Support aircraft (relay) will be extended range
version of UT-X2, tentatively called UT-X2E• Retrieval aircraft will be new airframe,
tentatively called UT-X3
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Competition Requirements-MedEx
University of Toronto Aerospace TeamUAV [email protected]
Configuration A (USC and AUVSI):• Primary camera: Genie TS-C4096• Secondary: Genie Nano C1940 or GmbH
VCSBC360• Communications: Rocket M5• UT-X2 airframe
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Competition Specific Configurations
University of Toronto Aerospace TeamUAV [email protected]
Configuration B (MedEx):Support Aircraft (S.A.)
• Primary camera: Genie Nano C1940 or GmbH VCSBC360
• Communications: standard transceiver - communicates with R.A. when R.A. is out of L.O.S. of PCS/GCS
• UT-X2E airframeRetrieval Aircraft (R.A.)
• Communications: standard transceiver• UT-X3 airframe
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Competition Specific Configurations
University of Toronto Aerospace TeamUAV [email protected]
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Primary CameraGenie TS-C4096
Secondary Camera
Payload Computer
Odroid XU4
Flight Transceiver
Rocket M5
Ground TransceiverNanostation M5
Flight Payload
Ground StationGround GUI, additional
processing
Ground Control
DATA LINK
Configuration A
University of Toronto Aerospace TeamUAV [email protected]
• Genie TS-C4096:– Resolution: 4096 x 3072– Max 12 fps, 200 g
• Genie Nano C1940:– Resolution: 1920 x 1200– Max 52 fps, 46 g
• GmbH VCSBC360:– Resolution: 4 x 752 x 480– Max 55 fps, 4 cameras for panoramic view
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Configuration A Rationale & Specs (1)
University of Toronto Aerospace TeamUAV [email protected]
• Primary camera takes high resolution images less frequently, secondary takes lower resolution images continuously
• High res. images for accurate image characterization
• Low res. images for localization and temporal classification algorithms
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Configuration A Rationale & Specs (2)
University of Toronto Aerospace TeamUAV [email protected]
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Primary CameraGenie Nano C1940
Payload Computer
Odroid XU4
Flight TransceiverPayload Data and
Telemetry
Ground Transceiver
Airgrid M5
Flight Payload
Ground StationGround GUI, additional
processing
Ground Control
DATA LINKS
TO R.A.
Configuration B - Support
University of Toronto Aerospace TeamUAV [email protected]
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Flight Telemetry
Ground Transceiver
Xtend 900
Flight Payload
Ground Station
Ground Control
WHILE AIRCRAFT IN L.O.S.
TO S.A.
Configuration B - Retrieval
University of Toronto Aerospace TeamUAV [email protected]
• Mission critical payload carried on support aircraft
• Lower resolution requirements, need to find Joe and land
• Genie Nano is four times lighter, better for range requirements (> 12 km)
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Configuration B Rationale & Specs
University of Toronto Aerospace TeamUAV [email protected]
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Progress
Phase A Phase B Phase C
JANUARY
MARCH
MAY
USC AUVSI
Phase D
SEPTEMBER
AUVSI MEDEX
University of Toronto Aerospace TeamUAV [email protected]
• Phase A: Initial development and prototyping• Phase B: Integration for USC and AUVSI• Phase C: Validation and testing & Integration for
MedEx• Phase D: Validation and testing for MedEx
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Progress
University of Toronto Aerospace TeamUAV [email protected]
Computer Vision:• New member training complete• Feature identification - 75% complete• Classification - 60% complete• Next steps: integration with onboard systems
Communications:• Training complete• Theoretical and Preliminary design - 85%
complete• Next steps: antenna tracker design,
validation/range-testing and integration with onboard systems
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Phase A Progress
University of Toronto Aerospace TeamUAV [email protected]
University of Toronto Aerospace TeamUAV [email protected]
COMPUTER VISION SUBDIVISIONLEAD: DAVIS WU (ECE 1T8)
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University of Toronto Aerospace TeamUAV [email protected]
• Identification/Cropping–To be sent to ground station via
communications
• Classification–Exploring Shape Context, Tesseract,
and Tensorflow
• User Interface–Built in Qt–Runs vision scripts from the ground
station 51
Tasks
University of Toronto Aerospace TeamUAV [email protected]
• QR Code Reader–Implemented in User Interface
• Segmentation–Required for some methods of
classification
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Tasks
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Identification Ini Output[Date]Date Analyzed = 2015-11-21 01:41:52
[Analysis Parameters]HAS_BLUR = 1MAX_AREA = 38000ACTIVE_CHANNEL = [1, 2]MIN_POINTS_IN_CLUSTER = 5BKS = 6MIN_AREA = 3500CROP_PADDING = 6IMAGE = IMG_0496.jpgSIZE_OF_ROI = 300USE_TREE_FILTER = 1Width = 3648Height = 2736FD Type = MSER
[Channel Keypoints]Channel 0 = 7Channel 5 = 5Channel 8 = 8
[Crop Info]Number of Crops = 9
[Crop 1]Image Name = IMG_0496 roi0.jpgX = 129Y = 1368Size = 192.0
[Crop 2]Image Name = IMG_0496 roi1.jpgX = 1416Y = 1295Size = 251.882943144
[Crop 3]Image Name = IMG_0496 roi2.jpgX = 2019Y = 677Size = 272.0
[Crop 4]Image Name = IMG_0496 roi3.jpgX = 762Y = 111Size = 181.071428571
[Crop 5]Image Name = IMG_0496 roi4.jpgX = 1183Y = 2437Size = 250.873449132
[Crop 6]Image Name = IMG_0496 roi5.jpgX = 3073Y = 99Size = 180.0
[Crop 7]Image Name = IMG_0496 roi6.jpgX = 272Y = 2165Size = 196.0
[Crop 8]Image Name = IMG_0496 roi7.jpgX = 2092Y = 443Size = 368.0
[Crop 9]Image Name = IMG_0496 roi8.jpgX = 2432Y = 171Size = 340.0
University of Toronto Aerospace TeamUAV [email protected]
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Segmentation
● Differentiates between different regions of the image (Background, Letter, Shape)
● Required/Preferred for Shape Context and OCR methods
University of Toronto Aerospace TeamUAV [email protected]
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Classification
● Soon…● In addition to our own experimentation, we
have Tom
University of Toronto Aerospace TeamUAV [email protected]
University of Toronto Aerospace TeamUAV [email protected]
COMMUNICATIONS SUBDIVISIONLEAD: HARRY LIANG (ECE 1T8)
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University of Toronto Aerospace TeamUAV [email protected]
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University of Toronto Aerospace TeamUAV [email protected]
Gains [dBi]• Transmit Antenna:
2.1• Receiving
Antenna: 2.1Transmit Power [dBm]
• EZUHF: 28
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Losses [-dBi]Transmit Loss:
0.44Receiving Loss:
0.44Max Polarization:
3Free Space (1km):
85
Link Budget: EZUHF
Received Power: -58.8 dBmMinimum Power: -112 dBm
University of Toronto Aerospace TeamUAV [email protected]
Gains [dBi]• Transmit Antenna:
2• Receiving
Antenna: 5.4Transmit Power [dBm]
• Xtend 900: 30
• Xtend 900: 30
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Losses [-dBi]Transmit Loss:
0.44Receiving Loss:
0.37Max Polarization:
3Free Space (1km):
91.5
Link Budget: Xtend 900
Received Power: -58 dBmMinimum Power: -100 dBm
University of Toronto Aerospace TeamUAV [email protected]
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5.8GHz Payload• Currently Owned Choices
– AirGrid (27dBi)
– NanostationM5 (16dBi)
University of Toronto Aerospace TeamUAV [email protected]
Gains [dBi]• Transmit Antenna:
16• Receiving
Antenna: 2Transmit Power [dBm]
• Nanostation: 27
• Rocket: 27
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Losses [-dBi]• Transmit Loss:
0.24• Receiving Loss:
0.44• Max Polarization:
3• Free Space (1km):
108
Link Budget: NanostationM5 and RocketM5
Received Power: -66.7 dBmMinimum Power: -94 dBm
Received Power: -66.7 dBmMinimum Power: -94 dBm
University of Toronto Aerospace TeamUAV [email protected]
• USC and AUVSI: Only Nanostation M5
–Beamwidth of 10°–High Rotation Speed
• MedEx–AirGrid: Beamwidth of 4°–Low Rotation Speed
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Antenna Tracker Specifications
University of Toronto Aerospace TeamUAV [email protected]
University of Toronto Aerospace TeamUAV [email protected]
Airframe Subsystem
Kevin Dong & Nathan Curiale
University of Toronto Aerospace TeamUAV [email protected]
Medical Express Competition Requirements
Retrieval aircraft must have • VTOL capability• flight range of 60 km • speed that enables
the mission to be completed within 1 hour
• ability and capacity to carry a cylindrical payload (20mm diameter, 100mm length, 100g weight)
University of Toronto Aerospace TeamUAV [email protected]
Selected Configuration
• Gasoline engine as the primary mode of propulsion
• Electric motors used only for takeoff and landing
University of Toronto Aerospace TeamUAV [email protected]
Weight Comparison and Goal
Need: • additional electric motors/batteries for VTOL• Gas engine/fuel for long-range flight• 30% reduction of aircraft weight (includes quad mod)• Reasonable since past Powered Flight/Western Aero
aircrafts all under 9lbs
University of Toronto Aerospace TeamUAV [email protected]
Initial Power Curves
Based on: • Estimated weight savings• Estimated aircraft drag values• Theoretical thrust relation
University of Toronto Aerospace TeamUAV [email protected]
Batteries and Motors
Selected motors with 5000 mAh batteries provide ~3 minutes of hover time at max throttle
University of Toronto Aerospace TeamUAV [email protected]
Proposed Structural Changes: Wing
• Full carbon fiber wing is quite heavy on this scale
• Use old techniques but keep in mind reliability and ease manufacture
• Concept – keep simple
University of Toronto Aerospace TeamUAV [email protected]
Proposed Structural Changes: Fuselage
• No nose landing gear is required
• No structural fuselage front is needed
• Weight savings from strength reduction
• Not fully decided yet – two options so far
• Full balsa truss • Non-structural
shell
University of Toronto Aerospace TeamUAV [email protected]
Proposed Structural Changes: Quad Frame
Carbon fiber rods connected with machined/premade/3D printed clamps with addition layers of carbon fiber
University of Toronto Aerospace TeamUAV [email protected]
Proposed Structural Changes: Motor Mounts
• Aluminum clamps with square platform
• Screws will be used for tightening clamp as well as securing the motor
University of Toronto Aerospace TeamUAV [email protected]
University of Toronto Aerospace TeamUAV [email protected]
FABRICATIONKEVIN XU
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University of Toronto Aerospace TeamUAV [email protected]
• Fixed up UTX-2• Stronger wing• Multi-payload support.• New OS motor.• Pitch downed H-stab
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Airframes for USC and AUVSI
University of Toronto Aerospace TeamUAV [email protected]
• New refined UTX-2A Block 2• Weight saving design• (Experimental) Flap• Space for USC payload drop
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Airframes for USC and AUVSI
University of Toronto Aerospace TeamUAV [email protected]
• Back up• One front fuselage ready to swap• Another front fuselage in parts (can be
assembled in 3hours)• Other small parts around the aircraft
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Airframes for USC and AUVSI
University of Toronto Aerospace TeamUAV [email protected]
• Under designing……• VTOL transitioning aircraft• Two similar airframes
• Retrieval and support• Weight saving• Reparability• New fabrication techniques will be
used• CNCed foam• ……
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MedEx Airframes
University of Toronto Aerospace TeamUAV [email protected]
• Nose ski gear• PixHawk wiring mount• Primary payload mount• Secondary payload mount• And more ……
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More stuff to fabricate
University of Toronto Aerospace TeamUAV [email protected]
• UTX-2 is flight ready
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Progress
Replace the broken parts of fuselage 3D printed strake
New 3D printed H-stab V-stab
joint
New OS
motor
Front FPV window Fixing EZUHF antenna
Replace all
broken servos
University of Toronto Aerospace TeamUAV [email protected]
• ‘New’ wing• We are fixing the UTX-1 wing• And it is almost good to go.
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Progress
Up coming week
Open the wing up
Replace the broken strap Layer up new patch Patch
upRe-wire
University of Toronto Aerospace TeamUAV [email protected]
• UTX-2A Block 2• Under construction.
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Progress
Next week
End of the month
As soon as we have carbon
fiber
Before end of this year
Assemble
Wiring
V-stab
Wing closing
Bottom wing layer up
H-stab closing
Fuselage assemble
Fuselage parts layer up
Fuselage parts cut
Top wing layer up
H-stab layer up
University of Toronto Aerospace TeamUAV [email protected]
• PixHawk wiring mount• All ready have a first version of product• Expecting a second iteration
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Progress
Design 3D printed product
2ed iteration design
Print out 2ed iteration
University of Toronto Aerospace TeamUAV [email protected]
• Payload mount• Primary payload mount is done.
• It is a fixed mount• Secondary payload is gimballed
• Set to finish before winter break
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Progress
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And more
3D printed strakes
H-stab washer
Antenna enclosure
Ski gear
More to come……
University of Toronto Aerospace TeamUAV [email protected]
University of Toronto Aerospace TeamUAV [email protected]
MECHANICAL
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Tracking Antenna• Orient antenna array in direction of
support aircraft
Requirements• Operate for full mission time (roughly 1.5
hours)• Set up takes less than 15 minutes• Maximum positioning error of ±2°• Effective range of 12 km• Must comply with radio regulations (ACMA
in Australia and CRTS in Canada)– if used in US must comply with FCC
regulations
Objectives1. Weather resistant (snow, light rain, wind)2. Quick adjustment speed
GCS
Support Aircraft
2°
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University of Toronto Aerospace TeamUAV [email protected]
Payload Drop
• Carry payloads and drop them on specific coordinates
USC Payload:Royale Velour 2 ply toilet paper roll (75 g)Image credit "Toiletpapier (Gobran111)" by Brandon Blinkenberg. Licensed under CC BY 2.5 via Commons - https://commons.wikimedia.org/wiki/File:Toiletpapier_(Gobran111).jpg#/media/File:Toiletpapier_(Gobran111).jpg
AUVSI Payload:8 oz. water bottle(226.8 g)Image credit 2016 Rules for AUVSI Seafarer Chapter’s 14th Annual Student UAS (SUAS) Competition DRAFT Revision 0.9X 91
University of Toronto Aerospace TeamUAV [email protected]
Payload DropRequirements1. Securely contain payload(s) during flight
– Three 90 g crop probe or– One 227 g water bottle
2. Quickly release payloads3. Fail Safe (Ex: power failure, ejection failure)
Objectives• Low complexity• Low weight• Use the same system for both competitions
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University of Toronto Aerospace TeamUAV [email protected]
System OverviewCommand from GCS
Microcontroller
Servo 1
Servo 2
Servo 3
Door 1
Hinge
Fuselage Underside
1
2
3
Forward
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University of Toronto Aerospace TeamUAV [email protected]
Section View (Front)
Torsion Spring
Servo Lockin
g Pin
Fixed Support
Door
Support Beam
Fixed Support
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University of Toronto Aerospace TeamUAV [email protected]
University of Toronto Aerospace TeamUAV [email protected]
AVIONICS SUBSYSTEMERIK CHAU
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University of Toronto Aerospace TeamUAV [email protected]
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Avionics Subsystem:
Ground Control Station
Flight Controller (Autopilot)
UAV Propulsion and Servo Motors
RC Transmitter
RC Receiv
er
Telemetry
ESC
Waypoint Data
UAV Health &
Performance
Sensors GPS
Airspeed
PID Controller
University of Toronto Aerospace TeamUAV [email protected]
University of Toronto Aerospace TeamUAV [email protected]
FLIGHT TERMINATION SYSTEM (FTS)
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University of Toronto Aerospace TeamUAV [email protected]
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FTS Overview• The Flight Termination System
(FTS): Our UAV’s new and improved failsafe system
• Motivation: Make our system compliant with the rules of the Medical Express UAV Challenge
• Abstract: Design of an independent on board diagnostic and flight termination system to ensure safety compliance with the MedEx rules.
University of Toronto Aerospace TeamUAV [email protected]
99
FTS Design Specification• Key requirements:
– Must automatically terminate flight upon:
• Crossing a Geofence boundary• Failure of any HW or SW implementing Geofence
breach detection• Failure of the autopilot when in autopilot control• Pressing of the kill switch
– Must be an independent onboard system
– Must activate in all operating modes – Cannot be overridden after activation
University of Toronto Aerospace TeamUAV [email protected]
100
FTS Diagnostics• The FTS will allow us to:
– Automatically diagnose our UAV for several faults
– Asses the validity of sensor data– Modify the UAV’s behavior based on
any detected faults• All diagnostics are categorized into 3
classes based on fault severity and remedial action
• All diagnostics can be disabled*
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101
Type I Diagnostics•Detect critical system failures•A failure will result in immediate flight termination•The system cannot recover after failure
• Diagnostics: (All competition requirements)– Flight Termination Switch Active– Horizontal Geofence Breach– Vertical Geofence Breach– FTS Controller State of Health– Autopilot State of Health
University of Toronto Aerospace TeamUAV [email protected]
102
Type II Diagnostics•Detect potentially critical system failures•Ensure the system’s ability to perform Type I Diagnostics•A failure will result in a controlled VTOL landing•The system will not recover after a failure unless it is manually overridden
• Diagnostics: (Not competition requirements)– Auto-Land Active– Horizontal & Vertical Soft Geofence Breach– GPS Performance, Rationality & Erratic– FTS, Avionics & Propulsion Voltage Low
University of Toronto Aerospace TeamUAV [email protected]
103
Type III Diagnostics•Detect non critical system failures•A failure will result in the UAV hovering •The system will attempt to recover after a failure•If the system cannot recover, the UAV will auto-land
• Diagnostics: (Not competition requirements)– Hover Mode Active– GPS Connection Lost– Telemetry Connection to GCS Lost– Inter UAV Connection Lost (Retrieval
Only)
University of Toronto Aerospace TeamUAV [email protected]
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Diagnostic Logic FlowchartNormal
Operation
Flight Termination HoverAuto - Land
Type I Diagnostics
Type II DiagnosticsPass
Fail
Type III DiagnosticsPassTelemetry &
Sensor Data
Fail Fail
Pass
Timeout
FTS Diagnostics
FTS Control
University of Toronto Aerospace TeamUAV [email protected]
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Why include all of these extra safety features?• Medical Express D2 Point
Breakdown:– 5/15 Points for Safety Approach– 4/15 Points for Innovative Features – 3/15 Points for Systems Design– 3/15 Points for Learnings from the
Project• After passing D3, only the top 20
teams from D2 qualify for the competition
• Free $400 Lidar for the top 20 teams from D2
University of Toronto Aerospace TeamUAV [email protected]
106
FTS Hardware System RC Transmi
tterRC
ReceiverPPM
EncoderServo Motors (X6)
FTSGPS
Pixhawk GPS
FTS Controller
TelemetryGCS
LED
Buzzer
Switch
Battery
Avionics Battery
Airspeed Sensor
Lidar or Sonar
I2C Splitter
Pixhawk Flight Controller
University of Toronto Aerospace TeamUAV [email protected]
• Implemented in a MATLAB Simulink model
• Consumes MAVlink telemetry data from the Pixhawk to make diagnostic determinations
• Modifies the control system based on the fault determination(s)
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FTS Logic Model
University of Toronto Aerospace TeamUAV [email protected]
108
FTS Geofence Breach Detection• Geofence Breach Detection Algorithm
– Separate Horizontal and Vertical Geofence Diagnostics
– Vertical: Simple out of range high check.– Horizontal:
• Implemented in MATLAB (Code)• Makes extensive use of the “inpolygon”
function
University of Toronto Aerospace TeamUAV [email protected]
109
FTS Software Implementation Strategy
Arduino Mega 2560
MATLAB
Simulink
MATLAB
Code MATLAB Function
Block
Arduino
Block Set
FTS Controller
Geofence Breach
Detection Algorithm
FTS Diagnostic
Logic Software
UART
C++
Pixhawk
Support
PixhawkFlight
Controller
University of Toronto Aerospace TeamUAV [email protected]
University of Toronto Aerospace TeamUAV [email protected]
VTOL CONTROL
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University of Toronto Aerospace TeamUAV [email protected]
• Controller: Pixhawk (1)• Platform: PX4• Based off of the Standard VTOL
configuration • Includes a Transition Mode Switch
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Flight Mode Transition Software
University of Toronto Aerospace TeamUAV [email protected]
• Independently tune the rotary and then fixed wing configurations
• Then tune transition parameters:– Transition Throttle– Blending Airspeed– Forward Transition Duration (Time)– Transition Airspeed
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Autopilot Controller Tuning Strategy
University of Toronto Aerospace TeamUAV [email protected]
University of Toronto Aerospace TeamUAV [email protected]
PROJECT MANAGEMENT
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University of Toronto Aerospace TeamUAV [email protected]
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Gantt ChartNov. Dec. Jan. Feb.
March April
Detailed Design
Programming
Ordering Parts
Design Validation
AssemblySystem
Integration
System Calibration
System Testing
Current
Progress
University of Toronto Aerospace TeamUAV [email protected]
University of Toronto Aerospace TeamUAV [email protected]
GCS SUBDIVISIONLEAD: JESSE WANG
115
University of Toronto Aerospace TeamUAV [email protected]
• Software system based around Mission Planner
• Serves as autopilot control center– Monitor aircraft
telemetry data– Control aircraft
via waypoints– Send and receive
data to/from competition server
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• Ground Control Station
University of Toronto Aerospace TeamUAV [email protected]
• Interoperability is (partially) mandatory this year
• Primary task: no-fly zone, aircraft position, aircraft IAS, and aircraft altitude are to be displayed by GCS and sent to competition server as telemetry data
• Secondary task: download and display server time and obstacle data, each at 1 Hz (threshold) or 10 Hz (objective); upload target data to server
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GCS/Interoperability (AUVSI)
University of Toronto Aerospace TeamUAV [email protected]
118
Sense, Detect, and Avoid (AUVSI)
• Avoid stationary/moving virtual obstacles manually (threshold) or autonomously (objective)
University of Toronto Aerospace TeamUAV [email protected]
• Interoperability task to be completed using Mission Planner plugin
–Access to telemetry data, waypoints• Test server provided by SUAS organizers
–Runs on Linux• SDA will likely be a standalone program
–More processing power available–Communicates with Mission Planner
via interoperability plugin119
Implementation
University of Toronto Aerospace TeamUAV [email protected]
120
Progress so far
• Test server successfully deployed and accessible from host machine
• Simple test plugin runs successfully
• Next steps:–Send/receive HTTP requests to server
from plugin–Add capability to display obstacles and
boundaries–Evaluate performance during real test
flight
University of Toronto Aerospace TeamUAV [email protected]
University of Toronto Aerospace TeamUAV [email protected]
SYSTEMS TESTINGLEAD: LU CHEN (INDY 1T8T1)
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University of Toronto Aerospace TeamUAV [email protected]
• 7ft by 7ft tangram mock target–One side painted red–One side painted green
• Can make:–Triangle–Square–Hexagon–Trapezoid–Rectangle
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Mock Targets
University of Toronto Aerospace TeamUAV [email protected]
• Alphanumeric text overlay on top of shape:
–Made of Bristol board–5 colours
»Can make all capital letters with:▪M, O, E, B, S
»Can make all lower case letters with:▪m, o, e, b, s, w
• Infrared Target for USC needed
Mock Targets
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University of Toronto Aerospace TeamUAV [email protected]
Other possible targets:• Made of large tarp painted in different
colours– Folded into shapes and pinned into place– Strips of coloured duct tape as
alphanumerical charactersQR Code
• Possible options:– Print at a shop (~$5 per square foot,
extremely expensive)– Make
» Figure out dimensions and print it on several different sheets of paper
» Use tape on a tarp (probably inaccurate)
Mock Targets
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University of Toronto Aerospace TeamUAV [email protected]
Major Dates:• April 13: Proof of flight video for MedEx
• April 22: Proof of flight video for USC• April 29 - May 1: USC competition• May 18: Proof of flight video, telemetry data, pilot safety log for AUVSI
• June 15: AUVSI competition• August 3: Documentary of 5 hours of autonomous flight for MedEx
High Level Testing Schedule
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University of Toronto Aerospace TeamUAV [email protected]
• Full USC Systems test late-March, early-April
–Video can be used for MedEx and USC video deliverables
–Need full autonomous takeoff and landing of all aircraft used in MedEx by this time
• Full AUVSI Systems test early to mid-May–AUVSI video deliverable, ensure UAV can
successfully complete all primary tasks in AUVSI
• Full MedEx Systems test late-August, early-September
–Need 5 hours of autonomous flight time by August 3
»30 minutes autonomous in one flight»>20km track distance in one flight
High Level Testing Schedule
126
University of Toronto Aerospace TeamUAV [email protected]
USC deliverable specifics:• USC Full Systems Test:
–Accurate telemetry data and computer vision: estimate crop surface area
–Computer vision: Read QR Code, determine crop geolocation
–Payload: detecting infrared target–Mechanical: Drop probes
High Level Testing Schedule
127
University of Toronto Aerospace TeamUAV [email protected]
AUVSI deliverable specifics• Fully autonomous flight, emergent task
–Max 3 manual takeovers/3 minutes of manual flight
–Re-tasking objective• Computer vision/comms/telemetry data: ID of targets, actionable intelligence, ADLC
–Real time autonomous identification• Mechanical: Air drop
High Level Testing Schedule
128
University of Toronto Aerospace TeamUAV [email protected]
MedEx deliverable specifics• Fully autonomous takeoff and landing
• Comms: Long distance/time flights• Telemetry: Landing distance
High Level Testing Schedule
129
University of Toronto Aerospace TeamUAV [email protected]
Test Flight Priorities:• Data for computer vision - before winter break
–Images of targets»Corner cases
–Border targets for USC–Combine target imagery with
telemetry data• Autonomous flight
–Autonomous takeoffs and landings • Communications
–Range–Consistency of signal
High Level Testing Schedule
130
University of Toronto Aerospace TeamUAV [email protected]
Test Flight Priorities • Combine telemetry, communications, computer vision data to perform necessary objectives (January to March)
–Estimate surface area–Location of targets–Real time autonomous target
identification• Combine telemetry, communications, computer vision, mechanical (January to March)
–Air drops
High Level Testing Schedule
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