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Issue #224 March 2009
Vision-Guided Robotics
A Next-Generation Balancing Robot
by Hanno Sander
Start | Parallax Propeller | ViewPort | The DanceBot | Frame Grabber | Real-Time Tracking | Line Following With A Camera | Track A Pattern | Find A Beer Bottle | Wrap Up | Sources & PDF
FIND A BEER BOTTLE
I believe all robot vision articles should include the beer-finding problem. Finding a specially colored beer bottle with a color camera is quite doable; however, you’re limited to a grayscale camera. You’re also not guaranteed that the beer bottle will be the brightest object in the room. There’s no line to follow. The beer bottle doesn’t have a distinctive pattern. The only available trait is the actual shape of the beer bottle.
Use the correlation algorithm to find the shape of the beer bottle in a typical cluttered environment, u. This algorithm uses brute force to match a desired template to all possible locations in the image. The location of the best match is the location of the beer bottle. The degree of match at any given point is the sum of absolute differences between the pixels of the template and the corresponding pixels of the area to match. To improve the robustness of the algorithm against changes in brightness and contrast, I preprocess the template and every possible match with an auto-level algorithm.
This algorithm does a good job of finding beer bottles. Photo 5 shows the target identified in a complex environment. However, the image of the bottle must be a close match to the template (i.e., its scale and orientation must be identical). With additional processing power, multiple templates could be searched in succession or parallel to more robustly identify the bottle. Once identified, a faster, less processor-taxing algorithm could be used to steer the robot to the beer bottle in real time.
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| Photo 5—The DanceBot is finding the location of a beer bottle. |
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