Gaze-Guided Control of an Autonomous Mobile Robot Using Type-2 Fuzzy Logic

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dc.authoridKocamaz, Adnan Fatih/0000-0002-7729-8322
dc.authoridCastillo, Oscar/0000-0002-7385-5689
dc.authoriddirik, mahmut/0000-0003-1718-5075;
dc.authorwosidKocamaz, Adnan Fatih/C-2820-2014
dc.authorwosidCastillo, Oscar/I-5578-2019
dc.authorwosiddirik, mahmut/R-7971-2019
dc.authorwosidOchoa, Patricia/JUV-7478-2023
dc.contributor.authorDirik, Mahmut
dc.contributor.authorCastillo, Oscar
dc.contributor.authorKocamaz, Adnan Fatih
dc.date.accessioned2024-08-04T20:46:00Z
dc.date.available2024-08-04T20:46:00Z
dc.date.issued2019
dc.departmentİnönü Üniversitesien_US
dc.description.abstractMotion control of mobile robots in a cluttered environment with obstacles is an important problem. It is unsatisfactory to control a robot's motion using traditional control algorithms in a complex environment in real time. Gaze tracking technology has brought an important perspective to this issue. Gaze guided driving a vehicle based on eye movements supply significant features of nature task to realization. This paper presents an intelligent vision-based gaze guided robot control (GGC) platform that uses a user-computer interface based on gaze tracking enables a user to control the motion of a mobile robot using eyes gaze coordinate as inputs to the system. In this paper, an overhead camera, eyes tracking device, a differential drive mobile robot, vision and interval type-2 fuzzy inference (IT2FIS) tools are utilized. The methodology incorporates two basic behaviors; map generation and go-to-goal behavior. Go-to-goal behavior based on an IT2FIS is more soft and steady progress in data processing with uncertainties to generate better performance. The algorithms are implemented in the indoor environment with the presence of obstacles. Experiments and simulation results indicated that intelligent vision-based gaze guided robot control (GGC) system can be successfully applied and the IT2FIS can successfully make operator intention, modulate speed and direction accordingly.en_US
dc.description.sponsorshipTUBITAK-BIDEB [2214/A]en_US
dc.description.sponsorshipThis research was funded by TUBITAK-BIDEB under grant 2214/A.en_US
dc.identifier.doi10.3390/asi2020014
dc.identifier.issn2571-5577
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85066831437en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.3390/asi2020014
dc.identifier.urihttps://hdl.handle.net/11616/98819
dc.identifier.volume2en_US
dc.identifier.wosWOS:000697686500003en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherMdpien_US
dc.relation.ispartofApplied System Innovationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjecteye gaze trackingen_US
dc.subjectinterval type-2 fuzzy logicen_US
dc.subjectvision systemen_US
dc.subjectmobile robotsen_US
dc.subjectintelligent controlen_US
dc.titleGaze-Guided Control of an Autonomous Mobile Robot Using Type-2 Fuzzy Logicen_US
dc.typeArticleen_US

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