autonomous soil investigator. what is the asi? designed to complete the 2013 ieee student robotics...
TRANSCRIPT
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Autonomous Soil Investigator
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What Is the ASI?
• Designed to
complete the 2013
IEEE student robotics challenge
• Collects "soil" samples from a simulated forest environment
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The ASI Solution
• Localizationo Hypobotso Sensor Input
• Traversalo Pathfindingo Wheels
• Collectiono Armao OpenCV / Inverse Kinematics
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Localization
Position and Orientation Awareness
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Localization sensors:
Four eye modules, each with• Infrared rangefinder
• Ultrasonic rangefinder
• Sweeping Servo Motor
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How was Localization implemented
Particle Filter:• Uses a cloud of discrete
hypotheses (Hypobots) of the robot's position
• Cloud mimics robot's intended motions
• Each time a measurement is performed, each hypothesis is weighted
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Localization lessons learned:
• Work with the robot's perception, rather than your own
• Robustness is more important than efficiency
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Pathfinder
New Data:• Localization• IMU• Pucks
Static Data:• Graph Data
Planning and Routing
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Pathfinders
Probabilistic
pathfinding
Planned Pathingvs.
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Probabilistic pathfinding
• Slow to navigate in X, Y, Theta space
• Cannot find tricky solutions
• Paths are often not optimal
• Non-Voronoi solutions
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• Quick to solutions
• Location specific conditions
• Trick solutions
• Custom GUI
Planned Pathing
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Collection
Target Acquisition
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OpenCV - Computer Vision tool library
Used to precisely locate samples
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Inverse Kinematics
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Hardware -- Panda Board
• Featureso Dual Core, 1.2 GHz ARM Processoro Ubuntu 12.04 Linux Nativeo USB Host Controller
• Purpose: High Level Computingo Localization Algorithmso Pathfinding Algorithmso Computer Vision
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Hardware -- Microcontroller
• Featureso Rapid prototypingo Common Tools
• Purpose: Lower Deck Computingo Ackerman geometryo PWM for servo & motor controlo ADC for infrared o Sonar sensor interfacing
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Architecture
Project Structure and Optimization
Collaboration Optimization
Operation Methodology
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Methodology
MESSENGER
CONTROL
MODE
BASE
Panda Board
Python
Arduino
C/C++
• Operations per mode
• Binds modules
• Messenger communication central
• Stages
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Methodology (continued)
• Polymorphism
• Transitions
• Tailored behaviors
Init
Abstract Mode
CollectLocalize Pathfinding. . .
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Collaboration
• Github
o Distributed workflow
o Quality
o Recovery
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TEAM IMAGE