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Development of the Dynamic Stereoscopic Long Range System to Analyze Collective Animal Behavior for Applications in the Control of Robotic Swarms Corbin Spells Mechanical and Aerospace Engineering April 17, 2015

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Page 1: Defense Ver. 2

Development of the Dynamic Stereoscopic

Long Range System to Analyze Collective

Animal Behavior for Applications in the Control

of Robotic Swarms

Corbin Spells

Mechanical and Aerospace Engineering

April 17, 2015

Page 2: Defense Ver. 2

Goals and Contribution

• Aimed to provide a mobile, accurate,

long range positioning system for the

study of collective animal behavior.

– Derive a novel calibration technique

– Produce an image processing software to

detect and classify animals in an image

• Study geese, bison, and bighorn sheep

to produce quantitative data on their

behavior within groups.

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One small step for robots?

• Survivability

– Removes the requirement of continuous

communication

– Animal species have survived harsh

environments for years

• Increased Efficiency

– Animal species are efficient through

evolution

– Identify strong and weak members in the

swarm

• Reduced Operating Cost

– 85% of space mission cost can be in

ground operations

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Collective Animal Behavior

• Study of coordination

between individuals

within a large group

• Three rules:

– Separation: avoiding contact and crowding with closest neighbors

– Alignment: steering towards a common average heading

– Cohesion: steering towards a common average position

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Ideal Stereoscopic System

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Ideal Stereoscopic Geometry Modified

for the DSLRS

• Modifications

– Rotation of

Right Camera

wrt to Left

Camera

– Focal Length

– Center Point

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Dynamic Stereoscopic Long Range

System (DSLRS)

• Quantitative analysis

• Qualitative analysis

• Non-invasive

• Capable of tracking

multiple targets

simultaneously

• Mobile

• Quick Set Up

• Durable in several

conditions/environments

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Components

• Two Nikon D7100 Digital Camera

– 24.1 Megapixels

– 6 FPS

• GoPro Hero3

– 240 FPS

• Manfrotto Three Way Tripod

Head

• Two Nikon Shutter Release

Cables

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Calibration

• Separated into

intrinsic and extrinsic

parameters

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Intrinsic Parameter: Center Point

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Intrinsic Parameter: Focal Length

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Extrinsic Parameter: Rotation

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*Using optimized detection parameters

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Optimizing Detection Parameters

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BRISK

MSER

SURF

SURF Miscorrelation

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3D Raw Data

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Verification

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Quadcopter Verification

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Planar Positioning

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Separation

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Alignment

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Cohesion

Separation (Meters)

Elapsed Time

(seconds)

Mean Minimum Maximum Standard Deviation

0 5.2965 0.22897 11.703 1.0005

1.6 5.3005 1.2138 11.449 0.9925

2.8 4.8441 0.6802 11.442 0.7890

5.7 5.0227 0.82242 11.439 0.9327

6.5 7.1522 0.58736 11.261 1.6389

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Bison

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Bison

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Bison

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Bison

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Bison

• Each separate color line

represents an individual

member’s path

• Bison appear to walk in a

single file line through the

snow

– May increase efficiency by reducing the effort for each member to generate own path

• The cyan star represents

the smallest member of

the herd

– Location with respect to larger members may be for an increase in protection against potential predators

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Bighorn Sheep

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Bighorn Sheep

• Markers outlined in

red represent

members standing

sentinel

• Green triangles

indicate the rams;

blue circles

indicate ewes and

lambs

• Provides time

incremented

statistical spacing

Separation (Meters)

Elapsed Time (Minutes) Maximum Minimum Mean Standard Deviation

0 20.527 1.087 5.826 5.281

11 9.445 1.338 4.532 2.412

26 11.903 1.676 5.696 3.605

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Conclusion

• DSLRS provide a method to achieve

quantitative results for separation,

alignment, and cohesion

– Mobile

– Accurate

• Software to reduce analysis time

• Verified using other positioning

methods

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Acknowledgements

• Advisor

– Dr. Andrew Ketsdever

• Committee Members

– Dr. Kyle Webb and Dr. Jon Pigage

• BioFrontiers

• Colorado Parks and Wildlife

• Significant contribution of knowledge

– Austin Ventura

• Volunteer Field Research

– Nick Weber and Brandon Costa

• Technical Support

– Luis Fúster, Slade Rodrigues, and Stefan Doucette

• Experience and lab environment

– Carlos Maldonado, Ryan Bosworth, Jake Graul, Mario Arias, Roser Ginebra, George Cunningham, Chris Pena, and Stephen Sloan

• Support outside of the lab environment

– My Family, roommates, and Maria Thomas

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