Rapidly-exploring Random Trees Algorithm
An example of rapidly-exploring random trees in 2-D
Ref: "Rapidly-Exploring Random Trees: A New Tool for Path Planning", Steven M. LaValle, 1998
%~~~~
% Code can also be converted to function with input format
% [tree, path] = RRT(K, xMin, xMax, yMin, yMax, xInit, yInit, xGoal, yGoal, thresh)
% K is the number of iterations desired.
% xMin and xMax are the minimum and maximum values of x
% yMin and yMax are the minimum and maximum values of y
% xInit and yInit is the starting point of the algorithm
% xGoal and yGoal are the desired endpoints
% thresh is the allowed threshold distance between a random point the the
% goal point.
% Output is the tree structure containing X and Y vertices and the path
% found obtained from Init to Goal
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% Written by: Omkar Halbe, Technical University of Munich, 31.10.2015
Citar como
Omkar Halbe (2026). Rapidly-exploring Random Trees Algorithm (https://la.mathworks.com/matlabcentral/fileexchange/53772-rapidly-exploring-random-trees-algorithm), MATLAB Central File Exchange. Recuperado .
Compatibilidad con la versión de MATLAB
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- AI and Statistics > Statistics and Machine Learning Toolbox > Cluster Analysis and Anomaly Detection > Nearest Neighbors >
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| Versión | Publicado | Notas de la versión | |
|---|---|---|---|
| 1.0.0.0 | Small bug fix. |
