Autonomous Surface Vehicle Project

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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 (Faculty Advisor)
• Justin Selfridge (Graduate Advisor)
• Stanton Coffey (Graduate Advisor)

• Team A

• Team B

• Brian Skoog
• John Lee
• Jeff Roper
• Paul Hart
• Stephanie Mccarthy
• Andrew Vaden

• John Bernas
• Eric Starck
• Jason Putman
• Kevin Mcleod

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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.
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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?