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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

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

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Sensors. Vol. 20

ISSN

1424-8220

e-ISSN

—

Svazek periodika

21

Číslo periodika v rámci svazku

10

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

14

Strana od-do

—

Kód UT WoS článku

000662523600001

EID výsledku v databázi Scopus

2-s2.0-85105734593