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Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Input: Initial and desired configuration of the robot, the maximum number of samples, Nmax
Output: Tree, T
1.
Add initial configuration as a node C1 to the tree, T
2.
For i = 1 to Nmax:
R = Random Coordinate (x, y)
Pick existing configuration Cp of the tree whose Coordinate P is closest to R in the geometric distance.
Calculate (WL, WR) that locomotes the robot from P to R where the geometric distance to R reduces the most to generate a new set of configurations {C}.
Add {C} to tree
Stop if any configuration of {C} is within a tolerable error range for both geometric distance and head orientation.