THE PRINT-SCAN Machine 3-D Spatial Mapping Device

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THE PRINT-SCAN Machine3-D Spatial Mapping Device

• Nia Cook
• Stephen Tan
• Anil Rohatgi
• Senior Design
• Final Report Presentation
• ECE4006
• Spring2005

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Introduction

• Project Goal
• Use of 3-D imaging techniques to measure the
  detailed physical structure of the interior of a
  confined space and map it into a virtual 3-D
  environment
• Prototype
• The PRINT-SCAN Machine

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Project Specifications

• 10cm10cm10cm cubic volume
• Ability to capture physical detail (preferably at
  the micron level)
• Ability to measure the size and shape of objects
• Ability to measure relative positions of multiple
  objects within the volume
• Cannot employ imaging techniques using x-rays

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Project Constraints

• Objects are stationary within volume
• Objects have low reflectivity
• Objects are not in contact with neighbor
• A four month time limit
• Design cannot exceed 500 budget

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Component List

• Sharp GP2D12 distance measuring sensor
• IR Mirrors
• HP Inkjet Printers
• HP 5-49A Ink Cartridges
• HP 5-29A Ink Cartridges
• D1984 Data Capture with WINDAQ software
• Constructed ten centimeter volume
• Driver Circuit (L298N and SN74LS04N)

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Theoretical Design
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Project Technical Details

• Box construction
• 10 cm cube with open top
• Tracks on inside to stabilize mirrors
• Flaps on box for data threshold segmentation
• Driver Circuit
• SN74LS04N inverter toggles the L298N H-bridge so
  that printer moves back and forth
• Function generator provides 100 mHz square wave
  as input
• Power supply inputs 7 8 V for reasonable
  printer head speed

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Project Technical Details

• Laser Sensors
• Read distance as a function of voltage
• Records voltages in Excel
• 10 cm to 80 cm range
• Mirrors
• Reflective for 850 nm laser sensor
• Angled at 45 degrees to reflect the laser beam to
  the object
• Incremented upwards to capture object height

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Prototype Design
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Data Reconstruction

• Sensor characterization
• Power regression line
• 8.0082x(-0.837)
• Correlation percent 99.64
• Inverse regression applied to data

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Data Reconstruction

• Data Imported from Microsoft Excel to Matlab for
  processing
• Data needs to be segmented into vertical
  divisions

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Data Reconstruction

• Matrix structure and corresponding coordinate
  values

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Data Reconstruction

• Three reconstruction techniques

Spline fit
Point cloud
Mesh Grid
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Data Reconstruction

• Video demonstration result
• Attempted to scan two rubber wheels staggered
  inside the volume
• Managed to reconstruct shape and location,
  however, recovering the spacing between the
  objects did not function.
• Errors were in the data, not in the data
  processing

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Lessons Learned

• Scheduling
• IR Sensor Interaction
• Power Drive
• Calculations

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Conclusion

• Although the device did not perform as well in
  real life as expected, there was adequate data to
  support proof of concept.
• With better equipment, and more funding, the
  design could be extended to achieve the optimal
  goals of the project.

Initial Specifications Achieved
Specifications
10cm3 confined volume (top open) The volume is approximately 10 cm3
Capture physical detail, at micron level The actual resolution of the sensors do not give the physical details of the object at the micron level
Measure size and shape of objects Our design outlines the shape of an object
Measure relative positions of multiple objects within the volume During our product demonstration, we employed two objects, we were able to calculate their positions relative to each other, and however mapping the spacing between the objects was a problem. Occlusion was not a factor.
Cannot employ imaging techniques using x-rays Our device design, does not employ any x-ray imaging techniques
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Questions?

• ??