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

• Type: Article in International Conference Proceedings Book
• Date: 2023

Authors

Matos, D (Author) Other; Mendes, J (Author) Other; Lima, J (Author) Other; Pereira, AI (Author) Other; Valente, A (Author) Other; Soares, S (Author) Other; Pedro Luís Cerqueira Gomes da Costa (Author) FEUP; Paulo Gomes da Costa (Author) FEUP

Conference proceedings International

Title: ROBOTICS IN NATURAL SETTINGS, CLAWAR 2022

Pages: 436-447

25th International Conference on Climbing and Walking Robots and Mobile Machine Support Technologies (CLAWAR)

PORTUGAL, SEP 12-14, 2022

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 1 Citation

Other information

Authenticus ID: P-00X-3V6

DOI: 10.1007/978-3-031-15226-9_41

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12