Position Estimator for a Follow Line Robot: Comparison of Least Squares and Machine Learning Approaches

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Position Estimator for a Follow Line Robot: Comparison of Least Squares and Machine Learning Approaches

Matos, Diogo / Mendes, João / Lima, José / Pereira, Ana I. / Valente, António / Soares, Salviano / Costa, Pedro / Costa, Paulo

Abstract

Navigation is one of the most important tasks for a mobile robot and the localisation is one of its main requirements. There are several types of localisation solutions such as LiDAR, Radio-frequency and acoustic among others. The well-known line follower has been a solution used for a long time ago and still remains its application, especially in competitions for young researchers that should be captivated to the scientific and technological areas. This paper describes two methodologies to estimate the position of a robot placed on a gradient line and compares them. The Least Squares and the Machine Learning methods are used and the results applied to a real robot allow to validate the proposed approach.

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Document information

Title :

Position Estimator for a Follow Line Robot: Comparison of Least Squares and Machine Learning Approaches

Additional title:

Lect. Notes in Networks, Syst.

Contributors:

Cascalho, José M. (editor) / Tokhi, Mohammad Osman (editor) / Silva, Manuel F. (editor) / Mendes, Armando (editor) / Goher, Khaled (editor) / Funk, Matthias (editor) / Matos, Diogo (author) / Mendes, João (author) / Lima, José (author) / Pereira, Ana I. (author)

Conference:

Climbing and Walking Robots Conference ; 2022 ; Ponta Delgada, Portugal September 12, 2022 - September 14, 2022

Published in:

Robotics in Natural Settings ; Chapter : 41 ; 436-447

Lecture Notes in Networks and Systems ; 530

Publication date :

2022-08-25

Size :

12 pages

ISBN :

978-3-031-15226-9 , 978-3-031-15225-2

ISSN :