Predicate-Based Model of Problem-Solving for Robotic Actions Planning

Oleksandr Tsymbal, Paolo Mercorelli and Oleg Sergiyenko
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Oleksandr Tsymbal: Faculty of Automatics and Computerized Technologies, Kharkiv National University of Radio Electronics, Nauki Avenue 14, 61166 Kharkiv, Ukraine
Paolo Mercorelli: Institute of Product and Process Innovation, Leuphana University of Lüneburg, Universitätsallee 1, D-21335 Lüneburg, Germany
Oleg Sergiyenko: Faculty of Engineering, Autonomous University of Baja California, Blvd. Benito Juárez, Mexicali 21280, Mexico

Mathematics, 2021, vol. 9, issue 23, 1-13

Abstract: The aim of the article is to describe a predicate-based logical model for the problem-solving of robots. The proposed article deals with analyses of trends of problem-solving robotic applications for manufacturing, especially for transportations and manipulations. Intelligent agent-based manufacturing systems with robotic agents are observed. The intelligent cores of them are considered from point of view of ability to propose the plans of problem-solving in the form of strategies. The logical model of adaptive strategies planning for the intelligent robotic system is composed in the form of predicates with a presentation of data processing on a base of set theory. The dynamic structures of workspaces, and a possible change of goals are considered as reasons for functional strategies adaptation.

Keywords: adaptation; problem-solving; robotics; predicates; manufacturing system (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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