Defense Ver. 2
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Transcript of 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
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.
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
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
Ideal Stereoscopic System
Ideal Stereoscopic Geometry Modified
for the DSLRS
• Modifications
– Rotation of
Right Camera
wrt to Left
Camera
– Focal Length
– Center Point
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
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
Calibration
• Separated into
intrinsic and extrinsic
parameters
Intrinsic Parameter: Center Point
Intrinsic Parameter: Focal Length
Extrinsic Parameter: Rotation
*Using optimized detection parameters
Optimizing Detection Parameters
BRISK
MSER
SURF
SURF Miscorrelation
3D Raw Data
Verification
Quadcopter Verification
Planar Positioning
Separation
Alignment
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
Bison
Bison
Bison
Bison
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
Bighorn Sheep
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
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
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