Complexity Reduction of the Three-Point Dubins Problem (3PDP) Via Symmetry Exploitation for Machine Learning Purposes

Abstract

This work proposes a machine learning approach for the Three-Point Dubins Problem (3PDP) based on classification and regression. The 3PDP is a path planning problem with Dubins curves through 3 waypoints. It is required to find the heading at the intermediate point and the form of the two Dubins paths joining the three points. Classification is used to select the correct path type (out of 18) to avoid the trial-and-error enumeration of all cases; regression is employed to have a good initial guess for finding the heading angle. Our results are used to improve and speed-up existing methods in terms of efficiency and accuracy