data matrix code word placement

data matrix code in word erstellen

word data matrix font

data matrix code in word erstellen

word data matrix

word data matrix,
data matrix code in word erstellen,
data matrix code word placement,
data matrix code in word erstellen,
data matrix word 2010,
word data matrix font,
data matrix word 2007,
data matrix code in word erstellen,
data matrix word 2010,
word data matrix,
word data matrix font,
data matrix code in word erstellen,
data matrix word 2007,
word data matrix,
data matrix word 2010,
data matrix code word placement,
data matrix code word placement,
word data matrix code,
data matrix word 2010,
word data matrix code,

word data matrix font,
word data matrix code,
data matrix word 2010,
data matrix code in word erstellen,
data matrix code word placement,
data matrix word 2010,
data matrix code in word erstellen,
data matrix code in word erstellen,
data matrix code in word erstellen,

The CORDIC (coordinate rotation digital computer) method is a successive approximation algorithm that is useful for calculating the trigonometric functions sine and cosine very ef ciently. CORDIC uses a sequence of vector rotations to calculate trigonometric functions with successive approximation. To conceptualize, consider the following graph-based technique for calculating sine and cosine: 1. Draw a vector on the x y plane with a magnitude of 1 and a phase of 0 as shown in Figure 8.7. 2. Begin rotating the vector counterclockwise until the desired angle is reached. Maintain a magnitude of 1 as shown in Figure 8.8. 3. Note the (x, y) coordinates at the desired angle. The sine is simply the y value, and the cosine is the x value (the hypotenuse is 1, so sin y/1 and cos x/1). This is illustrated in Figure 8.9. In a hardware implementation, the vector rotation is performed by making adjustments in increments of 90 degrees divided by successively larger powers of 2 (successively smaller angle increments) and updating the x y coordinates for each jump. The decision to add or subtract the current incremental value depends on where the algorithm is relative to the target angle. Thus, we successively

A point Q is contiguous to another point S over the set {P }, if three conditions are met: (i) S {P }, (ii) Q and {P } are visible, and (iii) Q can be continuously connected with S using only points of {P } A set is contiguous if any pair of its points are contiguous to each other over the set We will see that no memorization of contiguous sets will be needed; that is, while watching a contiguous set, the robot s only concern will be whether two points that it is currently interested in are contiguous to each other A local direction is a once-and-for-all determined direction for passing around an obstacle; facing the obstacle, it can be either left or right Because of incomplete information, neither local direction can be judged better than the other.

Lest I only tell one side of the story, I ll admit that she also gave up her sewing machine and gave a ton of her older clothes and some of our furniture to a consignment shop down the road She was boxing up the microwave one afternoon when I called a halt to the entire operation We gotta eat! We ve definitely sold enough of our things She paused I just want to make sure we don t go bankrupt So far I ve raised a lot of money for us This made me feel like we were trying to raise funds to buy a kidney for one of our children How much I asked Five thousand, give or take a few hundred I had to admit that it was impressive.

approach the desired angle in progressively smaller increments. The iterative equations are de ned as follows: xi 1 Ki Xi yi di 2 i yi 1 Ki yi xi di 2 i Ki (1 2 2i ) 1=2 Note that Ki is a xed value determined by the iteration stage and approaches 0.60725. . . as i approaches in nity. The decision term di is 1 if the target angle is greater than the cumulative angle (increase the angle by increasing y and decreasing x). Similarly, di is 21 if the target angle is less than the cumulative angle (decrease the angle by decreasing y and increasing x). In a practical application, the designer would calculate Ki ahead of time based on the number of iterations and apply this at the end of the calculation as a constant factor. For a theoretical proof of these equations, the reader may refer to one of the many papers published on the topic of CORDIC theory. For most implementations, the recursion operates on add/subtract and comparison operations, all of which can easily be performed in a single clock cycle. Thus, the algorithm will run much faster or for a given speed can be implemented with fewer gates than required by a Taylor approximation. The only multiply operations are those that occur once at the very end of the calculation and are constant factor multiplications that can be further optimized.

For the sake of clarity, assume the local direction is always left The M-line divides the environment into two half-planes The half-plane that lies to the local direction s side of M-line is called the main semiplane The other half-plane is called the secondary semiplane Thus, with the local direction left, the left half-plane when looking from S toward T is the main semiplane Figure 312 exempli es the de ned terms Shaded areas represent obstacles; the straight-line segment ST is the M-line; the robot s current location, C, is in the secondary (right) semiplane; its eld of vision is of radius rv .

If, while standing at C, the robot were to perform a complete scan, it would identify three contiguous segments of obstacle boundaries, a1 a2 a3 , a4 a5 a6 a7 a8 , and a9 a10 a11 , and two contiguous segments of M-line, b1 b2 and b3 b4 ..