Barrel Detection

The following approaches have been considered:

1. Image Acquisition & Color Identification (#1)
   • Find orange pixels (on barrel) with (Pixels) => Red - Green => High-Pass Threshold => (Orange pixels)
   • Find while pixels (on barrel) with (Pixels) => Saturation => Low-Pass Threshold => (White pixels)
   • (Orange pixels) => Blob seperation => Orange stripes (Bounding Boxes)
   • (Orange pixels) => Blob seperation => White stripes (Bounding Boxes)
   • {Orange stripes (Bounding Boxes), White stripes (Bounding Boxes)} => Blob merging => Barrels (Bounding Boxes)
2. Image Acquisition & Color Identification (#2)
   • Find orange pixels (on barrel) with (Pixels) => Red - Green => High-Pass Threshold => (Orange pixels)
   • Scan horizontal lines of image, starting from the bottom, and moving up. When currect scan line intersects a sufficient number of orange pixels, mark the orange segment of the line as being the bottom edge of a barrel. Once the bottom edge of a barrel is identified, ignore all pixels above the bottom edge. Continue scanning.
3. Distance-Map Acquistion & Shape Identification
   • Strategy
     1. Scan distances in front of robot by some method, obtaining a distance-map.
     2. Find/distinguish the "plateaus" of the graph. Mark each "plateau" as the near-edge/near-face of a barrel.
   • Methods to Obtain a Distance Map
     1. SICK
        • Obtains a distance-map along a line projected away from the robot.
        • Easy to implement programmatically.
        • Expensive hardware. May be able to get from the CS department
     2. Stereoscopic Imaging
        • Obtains a distance-map along a plane projected away from the robot.
        • Difficult to implement programmatically.
        • Requires two camcorders. Currently, we only have one.

A Note on Notation

In the above steps, items surrounded with parentheses are data. Other items are analyses or filters.