Detail publikace

Evolutionary Computation Techniques for Path Planning Problems in Industrial Robotics: A State-of-the-Art Review

JUŘÍČEK, M. PARÁK, R. KŮDELA, J.

Originální název

Evolutionary Computation Techniques for Path Planning Problems in Industrial Robotics: A State-of-the-Art Review

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

The significance of robot manipulators in engineering applications and scientific research has increased substantially in recent years. The utilization of robot manipulators to save labor and increase production accuracy is becoming a common practice in industry. Evolutionary computation (EC) techniques are optimization methods that have found their use in diverse engineering fields. This state-of-the-art review focuses on recent developments and progress in their applications for industrial robotics, especially for path planning problems that need to satisfy various constraints that are implied by both the geometry of the robot and its surroundings. We discuss the most-used EC method and the modifications that suit this particular purpose, as well as the different simulation environments that are used for their development. Lastly, we outline the possible research gaps and the expected directions future research in this area will entail.

Klíčová slova

evolutionary computation; evolutionary algorithms; path planning; industrial robots; robot manipulators

Autoři

JUŘÍČEK, M.; PARÁK, R.; KŮDELA, J.

Vydáno

4. 12. 2023

Nakladatel

MDPI

ISSN

2079-3197

Periodikum

Computation

Ročník

11

Číslo

12

Stát

Švýcarská konfederace

Strany od

1

Strany do

23

Strany počet

23

URL

Plný text v Digitální knihovně

BibTex

@article{BUT187199,
  author="Martin {Juříček} and Roman {Parák} and Jakub {Kůdela}",
  title="Evolutionary Computation Techniques for Path Planning Problems in Industrial Robotics: A State-of-the-Art Review",
  journal="Computation",
  year="2023",
  volume="11",
  number="12",
  pages="23",
  doi="10.3390/computation11120245",
  issn="2079-3197",
  url="https://www.mdpi.com/2079-3197/11/12/245"
}