THE PRINT-SCAN Machine 3-D Spatial Mapping Device Nia Cook Stephen Tan Anil Rohatgi Senior Design Final Report Presentation ECE4006 Spring2005

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

Project Specifications 10cm*10cm*10cm 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

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

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)

Theoretical Design

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

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

Prototype Design

Data Reconstruction Sensor characterization Power regression line: x^(-0.837) Correlation percent: 99.64% Inverse regression applied to data

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

Data Reconstruction Matrix structure and corresponding coordinate values

Data Reconstruction Three reconstruction techniques Point cloud Spline fit Mesh Grid

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

Lessons Learned Scheduling IR Sensor Interaction Power Drive Calculations

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 levelThe actual resolution of the sensors do not give the physical details of the object at the micron level Measure size and shape of objectsOur 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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