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Computer Vision: Parallelize or Paralyze
Team Purple Threads
CSE Capstone 2012
April 2012
Abstract
• Purple Threads• Project Description• Motivation• System Overview• First Steps• Target Drone Platform• Turret System• Final Status
Purple Threads
Top Row: Duc Tran, Aviral Shrivastava(Sponsor), Gabriel SilvaBottom Row: Nicholas Moulin, Craig Hartmann, Anthony Russo, Nadim Hoque
Project Description
• This project is a real world system of robots that visually demonstrates the benefits of parallelization for computer vision applications
Motivation
• Computer vision systems have a wide variety of applications, but are very processor intensive
• Parallelization allows the implementation of more advanced computer vision techniques by removing the bottleneck on the processor
System Overview
• Project consists of two different robots– Target Drone Platform
• Detect & track projectiles• Avoid projectiles
– Turret System• Detect & track the target • Hit target with foam darts
First Steps
• Requirement Elicitation– High Level– Low Level
• Hardware/Software Specification• Risk Management• Project Timeline• Budget• Configuring Development Environment
Target Drone Platform
• Hardware– Traxxas Slash VXL*– ArduPilot Mega w/ IMU Shield– ION Intel Atom Motherboard*– Microsoft Xbox 360 Kinect Sensor*
*Other names and brands may be claimed as the property of others
Target Drone Platform
• Software– EMGU CV 2.3.0
• Open CV Wrapper (C#)
– ArduRover• Code for ArduPilot
– Microsoft Robotics Developer Studio 4*– Kinect for Windows SDK v1.0*
*Other names and brands may be claimed as the property of others
Target Drone Platform
• Implementation– Assemble Target Drone
• Hardware Components• Power System
– Setup Wireless Access to Drone– Configure Drone Software Stack– Implemented Platform Services through
RDS
Target Drone Platform
• Implementation– Obtain RGB & Depth Image Data From
Kinect*– Projectile Detection
• Color Threshold
– Projectile Tracking– Collision Avoidance Algorithm
*Other names and brands may be claimed as the property of others
Target Drone Platform
• Setbacks– Foam dart too small to track accurately– Hardware too heavy for original shocks– Depth frame coordinates are offset from
RGB frame coordinates with no translation function
– Dr. Shrivastava crashed the car into a tree!
Turret System
• Hardware– USB Missile Turret– Microsoft Xbox360 Kinect Sensor*– Arduino Uno– Servos
• Software– OpenCV 2.3.1– Libfreenect– Ubuntu 10.04*
*Other names and brands may be claimed as the property of others
Turret System
• Implementation– Obtain RGB/Depth Images from Kinect*
Sensor– Object Detection
• Color Threshold• Cascade Classification
– C USB Turret Driver– Program Arduino to Control Servos– C NetDuino Driver
*Other names and brands may be claimed as the property of others
Turret System
• Implementation– Equations Created to Track Target
• Depth Disparity to Depth(ft)– d_feet = (disparity-824.8)/15.2– d_feet = (0.1236*tan((disparity/2842.5)+1.1863))*3.2808399
• Pixels per Foot depending on Depth– Pixels/Foot = -55.91836*log(d_feet)+177.49225974457
Turret System
• Setbacks– Original turret configuration not precise
enough– Unable to implement libfreenect driver on
PS3*– Turret caught on fire– Turret mounting unstable
*Other names and brands may be claimed as the property of others
Turret System
• Turret Tracking and Hitting a Moving Car
• http://youtu.be/r7ccvPGcY8U
Turret System
• Effect of Parallelization on Turret System
• http://youtu.be/D5yTRKgOykY
Final StatusMajor Deliverables
Deadline Status
Project Plan 9/26/2011 100%
Unparallelized Turret System
1/31/2012 100%
Unparallelized Target Drone
2/7/2012 100%
Parallelized Robots
2/20/2012 50%
Benchmark Results
2/28/2012 50%
Product Documentation
3/15/2012 100%
Final Delivery of System
3/15/2012 75%
Questions
?
Backup Slides
Turret System
• Implementation– Equations To Track Target
• Horizontal Rotation• Vertical Rotation