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Beginning with a moving average filter.
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Zac Staples
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May 24, 2014
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/* | ||
* I'd like to have a library I can call for basic filtering operations. | ||
* | ||
* Most sensors in small scale robotics are noisy. For example as a | ||
* mobile robot approaches a wall, an atached ulrasonic sensor should | ||
* give readings in cm similar to the list below | ||
* | ||
* 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, ...bump! | ||
* | ||
* but all too often the data will come back like this | ||
* | ||
* 11, 10, 6, 8, 7, 3, 5, 4, 1, 2, 1, ..bump! | ||
* | ||
* By filtering the raw data, via a moving average or other more | ||
* specialized filter we can use the noisy data as an input to our | ||
* filter and then the processed data will give us a better linear | ||
* output. This linear output still doesn't match the exact distance | ||
* to the wall, but it is a much closer approximation than the noisy | ||
* data and provides a better set of data for the robot to make | ||
* control decisions from. | ||
* | ||
*/ | ||
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#ifndef FILTER_h | ||
#define FILTER_h | ||
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//******************************************************************* | ||
//* MOVING AVERAGE | ||
//******************************************************************* | ||
class Moving_average | ||
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#endif |