Intelligent control of robotic manipulators: a comprehensive review

Technological advancements in robotics significantly impact the design of robotic manipulators and their control. Manipulators find applications in electrical, mechanical, and process industries to reduce labor and improve accuracy. Controlling manipulators is challenging because of their complex dy...

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Vydané v:Spatial Information Research Ročník 31; číslo 3; s. 345 - 357
Hlavní autori: Rawat, Devendra, Gupta, Mukul Kumar, Sharma, Abhinav
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Singapore Springer Nature Singapore 01.06.2023
Springer Nature B.V
대한공간정보학회
Predmet:
Algorithms
Artificial intelligence
Artificial neural networks
Control methods
Control systems
Database Management
Decision making
Earth and Environmental Science
Expert systems
Fuzzy logic
Geographical Information Systems/Cartography
Geography
Heuristic methods
Machine learning
Manipulators
Neural networks
Nonlinear dynamics
Offshore
Remote Sensing/Photogrammetry
Robot arms
Robot control
Robotics
공학일반
ANN
Metaheuristic algorithm
Robotic manipulators
Intelligent control
ISSN:2366-3286, 2366-3294
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Popis
Shrnutí:Technological advancements in robotics significantly impact the design of robotic manipulators and their control. Manipulators find applications in electrical, mechanical, and process industries to reduce labor and improve accuracy. Controlling manipulators is challenging because of their complex dynamics and nonlinear properties. Researchers are exploring many ways to implement the effective control method, including classical and modern techniques. In all the applications, robotic manipulators interact with the real world. Therefore, they require an understanding of input–output relations, which raises the need for intelligent control methods. The revolutionized growth in artificial intelligence has significantly influenced robotic manipulators' control. This paper presents a detailed review of intelligent control techniques implemented on robotic manipulator systems. These intelligent control methods include artificial neural networks, fuzzy logic control, expert systems, metaheuristic algorithm, machine learning control, etc. These intelligent methods for robotic manipulators have gained more attention because they emulate human intelligence, which finds application in diverse fields of science and engineering. In this paper, authors have investigated and compared metaheuristic algorithm and their application in robotic manipulators.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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https://doi.org/10.1007/s41324-022-00500-2
ISSN:2366-3286
2366-3294
DOI:10.1007/s41324-022-00500-2