Autonomous Quadricopter for Fire Detection Presenation

7/14/2019 Autonomous Quadricopter for Fire Detection Presenation

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Autonomous Quadricopter for Fire

Detection

By Sander Idelson

Project with Paper



Presentation Outline

Introduction Why Use a Drone?

Drone Limitations

The Parrot AR Drone 2.0

Fire Detection

Control Algorithm

Future Work

Conclusion



Introduction

In June 2013, a forest fire in Arizona killed 19 firefighters

The fire approached the team unexpectedly and theywere caught helpless

Goal – Program a drone to autonomously detect andtrack a forest fire

Keep fire fighters constantly aware of their surroundings



Why Use a Drone? Cost is low ~$300-5,000

Equipped with many sensors, cameras Small computers on-board

Wireless communication

Small size

No danger to humans



Drone Limitations

Laws Drones are not allowed above 400 feet

Some states do not allow drones

FAA regulation

Hot topic – people don’t “like” drones They are associated with attacks and spying

Weather and wind effect their use



Parrot AR Drone 2.0

Commercial drone - $300

Quadricopter design – stable and light

Can be driven with iPhone, Android apps out-of-the-box

Huge development community



Specifications

Weighs 0.96 lbs Made of carbon fiber and has protective foam

On-board 1 GHz Linux computer

2 color video cameras (720p and QVGA)

Full Inertial Measurement Unit

Broadcasts its own Wi-Fi network

Limits range

Extended with antenna Many other features



Programming

Hayes Modem Commands – AT*Commands Programmable from any language

NodeJS – Javascript serverside platform – “Node-ar-drone” library by Felix Geisendörfer

Large open Source Community Tough to program everything with Javascript – Callback

functions, asynchronous

Python – “python-ardrone” library by Bastion Venthur

Easier language to use More support

Better for creating programs



Calibration

Drone is inconsistent and prone to blowing around Time of turn calibrated for different angles

Linear and Quadratic functions were found (Quadwas better)



Fire Detection

Infrared Camera Preferred choice

Hardware connection to on-board computer toocomplicated

Color video Use on-board cameras

Perform frame filtering with OpenCV and SimpleCVlibraries

Try a few different current algorithms



Color Video Fire Detection

RGB Color Space Segmentation [15] - Binary Filter Worked for images, not as well in video

Depends on light

Rmean is often too low

RGB Static Thresholds [17] – Binary Filter

Needs to be calibrated to the amount of light Impractical for real world use

CIE L*a*b* Color Space Segmentation [14] – Binary Filter More uniform color space

Better results Frame Subtraction – Movement Filter

Fire flickers at roughly 10 Hz

Many more…



Object Detection

Once image is filtered… SimpleCV has function called “findBlobs”

Take average position of 5 largest blobs because fire is sparse

2-D distance measurement to fire (rough estimate) Take image and find blobs Turn drone theta degrees Take another image and find blobs Perform , c is pixel distance, r is distance to fire



Control System

Simple Control System Provides a base for a larger control system

Slides along fire at a safe distance

Just above tree line (~200 feet)

Sends GPS coordinates & video back to base Can be overridden to manual mode

Performs one or many of the fire detectionalgorithms

Checks if fire is moving with frame subtraction





Future Work – Fire Detection

Equipment changes Infrared camera – ideally

Aligned dual color cameras for 3-D detection

Better, more complex algorithms

Statistical and fuzzy logic algorithms (referenced in paper) Motion modeling and flicker detection

Smoke detection

Improved processing speed

Perform processing on-board

Optimized code and algorithms



Conclusion

Project lays foundation for a great control system More work is definitely needed

All of the code is shared on Github (Sanderi44/AR-Drone-Fire-Detection)

Would like to continue this project in the future If fire fighters had these drones helping them, it

could save lives and prevent tragedies like Arizona



Questions?



Sources J. Marshall, and J. Billeaud. "19 Firefighters Killed in Arizona Forest Fire." Yahoo! News. The Associated Press, 01 July 2013. Web. 24 July 2013.

<http://news.yahoo.com/19-firefighters-killed-arizona-forest-fire-165420995.html>.

"Wildfires - Dry, Hot and Windy."Environment Facts, Environment Science, Global Warming, Natural Disasters, Ecosystems, Green Living - National Geographic . NationalGeographic Society, n.d. Web. 24 July 2013. <http://environment.nationalgeographic.com/environment/natural-disasters/wildfires/>.

L. Epatko. "How Are Drones Used in the U.S.?" Web log post. PBS. PBS, 18 Apr. 2013. Web. 25 July 2013.

Parrot SA. N.p.: Parrot SA., n.d. AR.Drone 2.0. Parrot New Wi-fi Quadricopter- Specifications. Parrot SA, 2012. Web. 25 July 2013.

ARDrone API . Program documentation. ARDrone API . Vers. 2.0. Parrot DEVZONE, 2013. Web. 25 July 2013.

F. Geisendörfer, Node-ar-drone. Open-Source Computer software. GitHub. Vers. 2.0. Felix Geisendörfer, n.d. Web. 27 July 2013. <https://github.com/felixge/node-ar-drone>.

B. Venthur, Python-ardrone. Open-Source Computer software. GitHub. Vers. 1.0. Bastian Venthur, n.d. Web. 27 July 2013. <https://github.com/venthur/python-ardrone>.

OpenCV | OpenCV . Open-Source Computer software. OpenCV | OpenCV . Vers. 2.4.6. Itseez, 2013. Web. 27 July 2013. <http://opencv.org/>.

SimpleCV . Open-Source Computer software. SimpleCV . Sight Machine Inc., 2013. Web. 27 July 2013. <http://simplecv.org/>.

FFMPEG. Open-Source Computer software. FFmpeg . Vers. 2.0. N.p., n.d. Web. 27 July 2013. <http://www.ffmpeg.org/>.

T.H. Chen; P.H. Wu; Yung-Chuen Chiou, "An early fire-detection method based on image processing," Image Processing, 2004. ICIP '04. 2004 International Conferenceon , vol.3, no., pp.1707,1710 Vol. 3, 24-27 Oct. 2004

Toreyin, B.U.; Cetin, A.E., "Online Detection of Fire in Video," Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on , vol., no., pp.1,5, 17-22June 2007doi: 10.1109/CVPR.2007.383442

T. Celik, Kai-Kuang Ma, "Computer vision based fire detection in color images," Soft Computing in Industrial Applications, 2008. SMCia '08. IEEE Conference on , vol., no.,pp.258,263, 25-27 June 2008

T. Celik, "Fast and Efficient Method for Fire Detection Using Image Processing," ETRI Journal, vol. 32, no. 6, Dec. 2010, pp. 881-890.

T. Celik, Demirel, H.; Ozkaramanli, H.; Uyguroglu, M., "Fire Detection in Video Sequences Using Statistical Color Model," Acoustics, Speech and Signal Processing, 2006.ICASSP 2006 Proceedings. 2006 IEEE International Conference on , vol.2, no., pp.II,II, 14-19 May 2006

B.H. Cho; J.W. Bae; S.H. Jung, "Image Processing-Based Fire Detection System Using Statistic Color Model," Advanced Language Processing and Web InformationTechnology, 2008. ALPIT '08. International Conference on , vol., no., pp.245,250, 23-25 July 2008

S.Y. Foo, "A fuzzy logic approach to fire detection in aircraft dry bays and engine compartments," Industrial Electronics, IEEE Transactions on , vol.47, no.5, pp.1161,1171,Oct 2000

V. Vipin, "Image Processing Based Forest Fire Detection." International Journal of Emerging Technology and Advanced Engineering 2.2 (2012): 87-95.International Journal of Emerging Technology and Advanced Engineering . International Journal of Emerging Technology and Advanced Engineering. Web. 27 July 2013.

J. De la Riva, F. Pérez-Cabello& E. Chuvieco, (Eds) 2005 Proceedings of the 5th International Workshop on Remote Sensing and GIS Applications to Forest FireManagement: Fire Effects Assessment: 9-17 Universidad de Zaragoza. ISBN: 84-96214-52-4

L.Merino; Caballero, F.; Dios, J.R.M.-d.; Ollero, A., "Cooperative Fire Detection using Unmanned Aerial Vehicles," Robotics and Automation, 2005. ICRA 2005. Proceedingsof the 2005 IEEE International Conference on , vol., no., pp.1884,1889, 18-22 April 2005



Image Sources

http://www.slashgear.com/parrot-ar-drone-wifi-helicopter-

gets-augmented-reality-iphone-control-0567744/ http://forums.nasioc.com/forums/showthread.php?p=387

47159 http://www.ljmu.ac.uk/NewsUpdate/viewarticle/500/

http://news.nationalgeographic.com/news/2013/13/130725-drone-uav-uas-disposable-wildfire-storm-chasers/ http://www.geekosystem.com/mecam-personal-

quadcopter/ http://www.maniacstore.com/Parrot-AR-Drone-2.0-Price-

In-India.html T. Celik, Demirel, H.; Ozkaramanli, H.; Uyguroglu, M.,"Fire Detection in Video Sequences Using StatisticalColor Model," Acoustics, Speech and Signal Processing,2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on , vol.2, no., pp.II,II, 14-19May 2006

http://www.slashgear.com/parrot-ar-drone-wifi-helicopter-gets-augmented-reality-iphone-control-0567744/


http://forums.nasioc.com/forums/showthread.php?p=38747159


http://www.ljmu.ac.uk/NewsUpdate/viewarticle/500/

http://news.nationalgeographic.com/news/2013/13/130725-drone-uav-uas-disposable-wildfire-storm-chasers/


http://www.geekosystem.com/mecam-personal-quadcopter/


http://www.maniacstore.com/Parrot-AR-Drone-2.0-Price-In-India.html





































http://www.ljmu.ac.uk/NewsUpdate/viewarticle/500/



























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Autonomous Quadricopter for Fire Detection Presenation

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