Probabilistic trajectory planning method for an autonomous platform

Authors: Karaf S.M.
Published in issue: #9(62)/2021
DOI: 10.18698/2541-8009-2021-9-738
Category: Informatics, Computer Engineering and Control | Chapter: System Analysis, Control, and Information Processing, Statistics
Keywords: path planning, self-driving car, probabilistic method, Bayes theorem, color recognition, autonomous platform device, Stanley method
Published: 15.10.2021

A stand has been developed for testing and debugging recognition and pathfinding algorithms for autonomous transport platforms. The location of the autonomous platform and the points indicating the trajectory (control points) are determined using a color recognition algorithm. A probabilistic method for constructing the path of an autonomous platform through a given trajectory is considered. The Stanley method was used to find the angle of rotation of the front wheels of the transport platform after determining the trajectory. Control commands were written to a JavaScript Object Notation file and transmitted to a Raspberry Pi single-board computer using a Node-js server.

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