Transcript Autonomous Surface Vehicle Project

MAE 435 Project Design and Management II
19 October, 2011
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ASV MAE Team Members
Advisors
 Dr Gene Hou
 Justin Selfridge
 Stanton Coffey
(Faculty Advisor)
(Graduate Advisor)
(Graduate Advisor)
Team A
Team B
 Brian Skoog
 John Bernas
 John Lee
 Eric Starck
 Jeff Roper
 Jason Putman
 Paul Hart
 Kevin Mcleod
 Stephanie Mccarthy
 Andrew Vaden
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ASV ECE Team Members
Advisors
 Dr Chung-Hao Chen
(Faculty Advisor)
Students
 Nimish Sharma
 Justin Maynard
 Robert Tolentino
 Bibek Shrestha
 Sushil Khadka
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Autonomous Surface Vehicle-ASV
 What is it?
 Vehicle (boat) that can operate with no human interaction
 Why do we need them?
 ASVs can operate in environments that are dangerous to humans
(nuclear, biological, space, etc)
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Objective
 Improve current ASV for the Summer 2012 Association for
Unmanned Vehicle Systems International annual
RoboBoat Competition
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RoboBoat Competition
 Primary Tasks
 Speed Test

Locate and complete a
straight course as fast as
possible
 Navigation Test
 Navigate a course of buoys
with several turns and
obstacles
 Secondary Tasks
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Solution Approach
 Determine/purchase sensors that provide competitive
performance
 Determine a navigation logic
 Integrate all sensors
 Test and evaluate sensors and navigation logic
 Debug and modify as required
 Install electronics on boat
 Test and evaluate ASV
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Upgrades in Progress
 Computer Vision code
 LiDAR
 Sensor gimbal mount
 Navigation Logic
 New onboard computer
 Arduino integration
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Computer Vision
 Primarily for buoy color
detection
 Inputs directly to
onboard computer
 Vision information only
extracted when LiDAR
detects object
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LiDAR
 Light Detection And




Ranging
Primary Navigation
Sensor
Inputs directly to
onboard computer
240 degree FOV
5.2 meter radius
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Sensor Gimbal Mount
 Required to keep LIDAR
and cameras level
 Uses Ardupilot gyro and
accelerometer sensors to
detect motion
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Navigation Logic
 Defined scenarios based
on:
 Distance to buoys
 Color of buoys
 Approach angle
 LiDAR as primary sensor
 Computer Vision as
secondary sensor
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Navigation Logic Flow Chart
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New Onboard Computer
 Custom build/Watercooled
 Intel Core i3-2100T
 Low Power consumption
 Dual core/Hyperthreading Technology
 M4-ATX-HV DC-DC Power Converter
 250 Watts maximum
 6-34v DC wide input

Will run on boat battery
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Onboard Computer Cont.
Not to Scale
Inside Waterproof Box
HDD
Pump/
Reservoir
Power
CPU
RAM
Radiator
Motherboard
Wireless
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Arduino Integration
 Ardupilot integrated
sensors
 GPS
 Gyro
 Compass
 Accelerometer
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Sensor Schematic
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Gantt Chart
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Summary
 Improve current ASV in order to be more competitive




in RoboBoat competition primary tasks
Integrate LiDAR as primary navigation sensor
Build gimbal mount for navigation sensors
Integrate Ardupilot
Upgrade computer hardware to improve processing
speed and electronics case cooling
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Questions?
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