collision detection for vehicles with uncertainty in the position represented as a gaussian distribution
The implementation is based on an approximate but quick and accurate method.

import collide

Functions:

collide.collides(x1, y1, x2, y2, L1, W1, theta1, L2, W2, theta2)

collide.plot(x1, y1, x2, y2, L1, W1, theta1, L2, W2, theta2)

collide.collides(x1, y1, x2, y2, L1, W1, theta1, L2, W2, theta2, cov1, cov2, method, sample_size)



variables:

x,y: position

L,W: length and width

theta: angle of the vehicle in radian

In case of uncertinity:

define cov1, cov2: 2x2 array

method: 's':sampling with sample_size(has default value of 100), 'g' euclidean gaussian distribution, 'e' epsilon shadow

source-code: https://github.com/rashid1844/collides/