asp.net barcode reader Figure 5 15. The 2007 FLL Power Puzzle field mat in Font

Creating Data Matrix 2d barcode in Font Figure 5 15. The 2007 FLL Power Puzzle field mat

Figure 5 15. The 2007 FLL Power Puzzle field mat
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CHAPTER 5 LINE FOLLOWING AND DETECTION
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Now, when you count lines, remember that you cannot just count how many times your light sensor sees a black line, because as a light sensor travels over a line, it will read it multiple times. You will have to include edge-detection logic in your code, along the following lines: 1. 2. 3. 4. Look for a black line, or rather a black reading. Increment a counter when black is encountered. Begin looking for a transition to white, (i.e., for a white reading). Go back to step 1 when white is encountered.
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Once you find white, start looking for black again; this process would continue for however many lines you re expecting to encounter. In Figure 5 16, you can see an example of what such code would look like in NXT-G.
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Figure 5 16. An NXT-G line-counter program In this NXT-G line-counter code, the robot runs forward and waits for the Light sensor block to detect a black line. Then, the next Light sensor block will wait to find the next nonwhite area, letting us know that we have completely crossed the black line. When the loop counter reaches three, this Loop block exit and the Move block at the end will stop the robot.
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Detecting Color in Lines
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You will notice that, on the field mats in Figures 5 14 and 5 15, many of the lines or areas are not simple black-and-white lines; actually, many of them are colored lines or edges. Even though we re using the NXT Light sensor and not the NXT Color sensor, we can still detect different colors. We do so by interpreting the different colors as shades of grey. The values returned for a given color will fall somewhere in the spectrum between 0 for white and 100 for black. Ideally, you will still be able to calibrate your Light sensor on a white-and-black source, and the color values will fall between the calibrated range of 0 100. It is best to first calibrate your Light sensor, and then by using the light value view program place your light sensor over the various colors on the game field map and use the light value view program to read and record the values for each color. As long as you can calibrate your robot consistently the color values should be read the same. Be careful! Some colors will share the same value. For example, many times red, green, and gray will return the same intensity values to the NXT Light sensor. This is why it is important to get a good reading on each color and keep track of which values register the most consistent results. Also, when you are thinking through your strategies for navigating a game field, look for colors that contrast more drastically with other colors to help avoid confusion and make finding the navigation
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CHAPTER 5 LINE FOLLOWING AND DETECTION
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points easier. Thick lines are, of course, going to make better markers than thin or fussy lines and edges. You are really looking for anything unique that can produce consistent readings back to your program. Consistent markings are going to produce consistent results.
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Light Sensors are one of the most helpful sensors when trying to navigate most robotics game fields. In FLL the game field maps are full of clues that can be utilized by Light Sensors. Many teams will shy away from using them just because they have a bit of a learning curve when first using them. But almost all winning teams take advantage of Light Sensors when navigating the field.
CHAPTER 5 LINE FOLLOWING AND DETECTION
CHAPTER 6
Squaring Up
After learning about going straight and turning, you re now able to give your robot just enough information to get seriously lost on the game field. No matter how well your robot navigates in any direction, it won t take long before it loses track of where it is facing. This is just the nature of LEGO robots; they re never going to be consistently accurate without a little help and some realignment. When your robot starts running a few missions, you ll notice that after just a few navigation changes, such as going straight, turning 90 degrees, going straight again, and then maybe backing up, it will rarely end up in the exact same place again, much less be pointing in the same direction each time. When you plan your robot s missions, it s always a good idea to build in some expectations of error by about an inch. Doing so will be important when you re thinking through your strategies for completing a mission. But there also ways to use your environment to get your robot pointing in the right direction even after you ve left base. Winning robots will constantly realign themselves throughout the game to ensure consistency for each mission they attempt. The trick is to locate the points on the game field that your robot can align with to get the best results. You re looking for anything that is a constant on the field, things that don t move and remain in the same position relative to the rest of the field at all times. Such things can be markers printed on the game field, such as lines or shapes or the actual walls of the game table itself, which can be very useful when the game mat is lined up properly on the table. Or there could be actual field objects that are affixed to the mat throughout the game and won t be moving or removed. When you are coming up with your mission strategies, think about things that can help you square up your robot again after just a few moves. Is there a wall close by after you make a 90-degree turn What about the field mat; is there some kind of line or border that your robot can try to detect and line up with Maybe the mission object itself has some way for you to use it to square up before or after you ve completed the mission. These are all things you want to think about as you do your planning. They will be the keys to having successful and accurate robot runs.
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