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Python Code || Path Planning with Grey Wolf Optimization (GWO) ~xRay Pixy

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Learn how to implement an obstacle-avoiding path planning for a robot using the Grey Wolf Optimization (GWO) in a static environment. #optimization #algorithm #metaheuristic #robotics #deeplearning #ArtificialIntelligence #MachineLearning #computervision #research #projects #thesis #Python
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Line Drawing Algorithm

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 Line Drawing Algorithm

We can specify points with an ordered pair of numbers ( x, y).

Where, x = horizontal distance from the origin.

     y = vertical distance from the origin. 

Suppose 2 endpoints used to specify line at position (x1, y1) and (x2, y2).

Line path between endpoints positions (x1, y1) and (x2, y2).

The equation for straight line is given by:

y = m . c + b

Here, m = slope of the line

           b  as y-intercept

The first endpoint of the line as (x1, y1)

The second endpoint of the line (x2, y2)

We can calculate values for the slope m and y-intercept b with this equation:

𝑚=(𝑦2−𝑦1)/(𝑥2−𝑥1)

b = y1 – m * x1.

For any given x interval ∆x along a line.

We can compute the corresponding y interval as ∆y as

∆y =m * ∆x 

We can obtain x interval ∆x by ∆y. 

∆x = ∆y / m 

DDA Algorithm

Step 1. Input two Endpoints (x1, y1) and (x2, y2).

Step 2: Calculate the difference between two endpoints. 

𝑑𝑥= 𝑥2−𝑥1 and dy = y2−𝑦1

Step 3: Identify the number of steps required to put pixel.

                 if (dx > dy)

                   {

              Add more steps in x coordinate. 

          }

Otherwise y coordinate. 

Step 4: Calculate the increment in x and y coordinates.

Step 5: Put the Pixel by successfully incrementing x and y coordinates. 

Step 6: Complete the Line Drawing. 


Video Link: https://youtu.be/wzxQjBgQDzc

 


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