Speed control for leader-follower robot formation using fuzzy system and supervised machine learning

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F21%3A10247460" target="_blank" >RIV/61989100:27240/21:10247460 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/1424-8220/21/10/3433" target="_blank" >https://www.mdpi.com/1424-8220/21/10/3433</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/s21103433" target="_blank" >10.3390/s21103433</a>

Result language

angličtina

Original language name

Speed control for leader-follower robot formation using fuzzy system and supervised machine learning

Original language description

Mobile robots are endeavoring toward full autonomy. To that end, wheeled mobile robots have to function under non-holonomic constraints and uncertainty derived by feedback sensors and/or internal dynamics. Speed control is one of the main and challenging objectives in the endeavor for efficient autonomous collision-free navigation. This paper proposes an intelligent technique for speed control of a wheeled mobile robot using a combination of fuzzy logic and supervised machine learning (SML). The technique is appropriate for flexible leader-follower formation control on straight paths where a follower robot maintains a safely varying distance from a leader robot. A fuzzy controller specifies the ultimate distance of the follower to the leader using the measurements obtained from two ultrasonic sensors. An SML algorithm estimates a proper speed for the follower based on the ultimate distance. Simulations demonstrated that the proposed technique appropriately adjusts the follower robot&apos;s speed to maintain a flexible formation with the leader robot. (C) 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Sensors. Vol. 20

ISSN

1424-8220

e-ISSN

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Volume of the periodical

21

Issue of the periodical within the volume

10

Country of publishing house

CH - SWITZERLAND

Number of pages

14

Pages from-to

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UT code for WoS article

000662523600001

EID of the result in the Scopus database

2-s2.0-85105734593