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Uav image recognition technology and applications

Date post: 15-Jun-2015
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Tejas P. Kulkarni - Cockrell School of EngineeringPresented at the 2011 Texas GIS Forum
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UAV Image Recognition Technology and Applications The UT UAV Group Cockrell School of Engineering The University of Texas at Austin Harmony MonesMurphy Chockalingam Viswanathan Tejas Kulkarni
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Page 1: Uav image recognition technology and applications

UAV Image RecognitionTechnology and Applications

The UT UAV GroupCockrell School of EngineeringThe University of Texas at Austin

Harmony Mones‐MurphyChockalingam Viswanathan

Tejas Kulkarni

Page 2: Uav image recognition technology and applications

What is a UAV?

• The Department of Defense Dictionarydefines a UAV as:A powered, aerial vehicle that does not carry a human operator, uses aerodynamic forces to provide vehicle lift, can fly autonomously or be piloted remotely, can be expendable or recoverable, and can carry a lethal or nonlethal payload. 

Page 3: Uav image recognition technology and applications

Driving Technology• Powered heavier than air flight• Radio control (R/C)• Autopilots• GPS• Imagery systems• High density power batteries• Long range and low‐power micro radio devices• Miniaturized parts• Wireless networks• Powerful micro‐processors

Page 4: Uav image recognition technology and applications

HISTORICAL FIRSTS

1898 1933

1903

1912

1918 1959

1960

Page 5: Uav image recognition technology and applications

1898: First demonstration of radio‐control 

Nikola Tesla’s “Teleautomaton,” a radio‐control boat 

Electrical Exposition at Madison Square Garden

Page 6: Uav image recognition technology and applications

1912: First autopilot

Elmer and Lawrence Sperry

• A gyrostabilizer hydraulically operated the elevators and rudder.

• Allowed the aircraft to fly straight and level without pilot input.

Curtiss B‐2

Page 7: Uav image recognition technology and applications

1918: First radio‐controlled unmanned flight

Curtiss‐Sperry Aerial Torpedo

• Forerunner of the modern cruise missile. 

Page 8: Uav image recognition technology and applications

1959: First unmanned reconnaissance aircraft

Northrop Radioplane SD‐1 Falconer/Observer

Page 9: Uav image recognition technology and applications

TYPES OF UAVS

Page 10: Uav image recognition technology and applications

Fixed‐Wing

Northrop Grumman RQ‐4 Global Hawk

Page 11: Uav image recognition technology and applications

Rotorcraft

Helicopter: Northrop Grumman MQ‐8 Fire Scout

Quadcopter Tiltrotor: Bell Eagle Eye

Page 12: Uav image recognition technology and applications

PAYLOADS

Page 13: Uav image recognition technology and applications

Electro‐optic Payload Systems

• Optical Cameras• Low‐light‐level 

(LLL) Cameras• Thermal Imagers

Page 14: Uav image recognition technology and applications

Radar Imaging Payloads

• Synthetic Aperture Radar(SAR)

Page 15: Uav image recognition technology and applications

Dispensable Payloads

• Civil ‐ Pesticides

• Military – Missiles

Page 16: Uav image recognition technology and applications

UT UAV

Page 17: Uav image recognition technology and applications

Our Team

• Undergraduate• Interdisciplinary• Student leadership

Page 18: Uav image recognition technology and applications

AUVSI Competition

• Student UAS Competition in Maryland

• Reconnaissance mission

• Fourth year of participation

• 1st in Autonomous Target Recognition in 2010 

Page 19: Uav image recognition technology and applications

Phoenix II

Imagery

AvionicsAirframe

Page 20: Uav image recognition technology and applications

UT UAV Overview• Our Implementation

– Target Detection– Target Analysis– Position Determination

Page 21: Uav image recognition technology and applications

Target Characteristics

• Position (LLA) • Background Shape• Background Color• Alphanumeric

Character• Alphanumeric Color• Orientation

4 to 8 feet

4 to 8 feet

Page 22: Uav image recognition technology and applications

Target Detection

• Color‐based approach– Outlier image

• Exploit target attributes– Size, aspect ratio

• Implemented on DSP– Texas Instruments C6748

Page 23: Uav image recognition technology and applications

Background Image

• Represent image  in 3‐D color space– , 

• Image contains background and foreground

Page 24: Uav image recognition technology and applications

Foreground Image

• Average RGB pixels in frame

• Compute distance from mean• Distance threshold determines potential targets

0 50 100 150 200 2550

0.02

0.04

0.06Red Plane

Per

cent

0 50 100 150 200 2550

0.02

0.04Green Plane

Per

cent

0 50 100 150 200 2550

0.02

0.04

Pixel Intensty

Blue Plane

Per

cent

Page 25: Uav image recognition technology and applications

Outlier Image

• Potential targets highlighted in oultlierimage

Original Image Outlier Image

Page 26: Uav image recognition technology and applications

Binary Image

• Remove noise ‐ windowed median filter• Label objects ‐ connected component

Binary Image Label Image

Page 27: Uav image recognition technology and applications

Target Analysis

CroppedImage

Segmentation Skeleton BoundingRectangle Rotate Compare

Page 28: Uav image recognition technology and applications

Target Detection Performance• Tested on scaled airfield and recorded video– Robust to trees, runways– Poor at detecting some colorsSpecification Performance

Speed 10 frames per second

Detection Accuracy* 85%

False Positive Rate 10%

* Accuracy = ratio of targets detected to total number of targets

Page 29: Uav image recognition technology and applications

Results

Legend:      Correct      Incorrect       Marginally Incorrect 

Page 30: Uav image recognition technology and applications

Target Position Determination

• Convert image coordinates to absolute position

• Position Accuracy– Maximum allowable error – 150 feet– Desired error – less than 50 feet

• Monte Carlo Error Analysis– Sweep camera 60 degrees in all directions from the vertical

– Estimate standard deviation of error

Page 31: Uav image recognition technology and applications

Monte Carlo Error Analysis

-750 -500 -250 0 250 500 750 1000-1000

-750

-500

-250

0

250

500

750

1000Error Analysis (500 feet altitude)

feet

feet

Standard Deviation (feet)

15

20

25

30

35

40

45

Page 32: Uav image recognition technology and applications

System Overview

Triangle J Purple

Yellow NW Lat Lon

Sony FCB EX‐980S 

TexasInstruments 

C6748

Target AnalysisLabVIEW

Page 33: Uav image recognition technology and applications

Plans for 2012

• Communication– Switch to Wifi (802.11N)

• Digital camera (DSLR)

• Weight reduction

Page 34: Uav image recognition technology and applications

Why UAVs?

• UAVs are suited for doing the “dull, dirty and dangerous” tasks of everyday life.

Page 35: Uav image recognition technology and applications

Applications of UAVs in Texas

• Oil & gas• Wildfires• Ranching

Page 36: Uav image recognition technology and applications

Oil & Gas

Use as a method to collect and transmit data between rigs

Use to check pipelines for leaks 

Page 37: Uav image recognition technology and applications

Wildfires

Bastrop County Wildfire

Aid Firefighters with real time information and firefighting 

capability. 

Page 38: Uav image recognition technology and applications

Ranching

Check fences for holes

Use to track cattle/deer

Spraying crops with pesticide and fertilizer, monitoring crops, soil, moisture, and pest conditions, and insect sampling

Page 39: Uav image recognition technology and applications

Safety

• Due to safety concerns there are strict regulations regarding the use of UAV’s in unrestricted airspace throughout the world. 

Page 40: Uav image recognition technology and applications

Air Systems Lab

• All the work done in the Air systems lab are undergraduate student projects, for various competitions. 

Page 41: Uav image recognition technology and applications

Q&A

Page 42: Uav image recognition technology and applications

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