Hybrid spiral stc-hedge algebras model in knowledge reasonings for robot coverage path planning and its applications

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dc.authorid0000-0002-4846-2584en_US
dc.authorid0000-0002-5928-0807en_US
dc.authorid0000-0001-6732-7575en_US
dc.authorid0000-0002-3470-9646en_US
dc.contributor.authorVan Pham, Hai
dc.contributor.authorAbut, Nurettin
dc.contributor.authorKandilli, İsmet
dc.date.accessioned2024-07-12T20:58:23Z
dc.date.available2024-07-12T20:58:23Z
dc.date.issued2019en_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.description.abstractRobotics is a highly developed field in industry, and there is a large research effort in terms of humanoid robotics, including the development of multi-functional empathetic robots as human companions. An important function of a robot is to find an optimal coverage path planning, with obstacle avoidance in dynamic environments for cleaning and monitoring robotics. This paper proposes a novel approach to enable robotic path planning. The proposed approach combines robot reasoning with knowledge reasoning techniques, hedge algebra, and the Spiral Spanning Tree Coverage (STC) algorithm, for a cleaning and monitoring robot with optimal decisions. This approach is used to apply knowledge inference and hedge algebra with the Spiral STC algorithm to enable autonomous robot control in the optimal coverage path planning, with minimum obstacle avoidance. The results of experiments show that the proposed approach in the optimal robot path planning avoids tangible and intangible obstacles for the monitoring and cleaning robot. Experimental results are compared with current methods under the same conditions. The proposed model using knowledge reasoning techniques in the optimal coverage path performs better than the conventional algorithms in terms of high robot coverage and low repetition rates. Experiments are done with real robots for cleaning in dynamic environments.en_US
dc.identifier.citationVan Pham, H., Asadi, F., Abut, N. ve Kandilli, İ. (2019). Hybrid spiral stc-hedge algebras model in knowledge reasonings for robot coverage path planning and its applications. Applied Sciences, Molecular Diversity Preservation International. 9(9).en_US
dc.identifier.issn2076-3417
dc.identifier.issue9en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://www.mdpi.com/2076-3417/9/9/1909/htm
dc.identifier.urihttps://hdl.handle.net/20.500.12415/3172
dc.identifier.volume9en_US
dc.institutionauthorAsadi, Farzin
dc.language.isoenen_US
dc.publisherMolecular Diversity Preservation Internationalen_US
dc.relation.ispartofApplied Sciencesen_US
dc.relation.isversionof10.3390/app9091909en_US
dc.relation.publicationcategoryUluslararası Hakemli Dergide Makale - Kurum Öğretim Elemanıen_US
dc.rightsCC0 1.0 Universal*
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.snmzKY00314
dc.subjectsimulation of a roboten_US
dc.subjectspiral spanning tree coverageen_US
dc.subjectrobot coverage path planningen_US
dc.subjecthedge algebraen_US
dc.subjectrobot knowledge reasoningsen_US
dc.titleHybrid spiral stc-hedge algebras model in knowledge reasonings for robot coverage path planning and its applicationsen_US
dc.typeArticle
dspace.entity.typePublication

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