Social navigation framework for assistive robots in human inhabited unknown environments

Basit Öğe Kaydı
dc.authoridYAVUZ, SIRMA/0000-0001-8029-6689
dc.authoridKose, Hatice/0000-0003-4796-4766
dc.authoridCakmak, Furkan/0000-0001-5232-7919
dc.authoridKivrak, Hasan/0000-0002-3782-309X
dc.contributor.authorKivrak, Hasan
dc.contributor.authorCakmak, Furkan
dc.contributor.authorKose, Hatice
dc.contributor.authorYavuz, Sirma
dc.date.accessioned2024-09-29T15:57:35Z
dc.date.available2024-09-29T15:57:35Z
dc.date.issued2021
dc.departmentKarabük Üniversitesien_US
dc.description.abstractIn human-populated environments, robot navigation requires more than mere obstacle avoidance for safe and comfortable human-robot interaction. Socially aware navigation approaches become vital for deploy-ing mobile service robots in human interactive environments, where the robot operates in interaction with human implicitly or explicitly. These approaches aim to generate human-friendly paths in human-robot interactive environments considering social cues and human behaviour patterns. This paper proposes a social navigation framework for mobile service robots, maintaining humans' safety and comfort while navigating towards the goal location in human interactive environments. Our main contribution is that the presented social navigation framework is designed to be used in human interac-tive unknown environments. To achieve this goal, we use a variant of a pedestrian model called Collision Prediction based Social Force model (CP-SFM). This model is particularly developed for low or average density environments and takes the motion of the people tracked in the environment into account during the navigation. The model is employed as a local planner to generate human-friendly plausible routes for our service robot in corridor like indoor environment scenarios. A variety of different extensions and improvements of the conventional social force model are employed in the implementation stage. A novel improvement in producing multi-level mapping, identifying obstacle repulsion points and adopting CP-SFM for application in motion planning as local task solver is presented. The whole framework has been implemented as ROS nodes, and tested both in real world and simulation environments and successfully verified based on the obtained results. (C) 2020 Karabuk University. Publishing services by Elsevier B.V.en_US
dc.description.sponsorshipTurkish Scientific and Technical Research Council (TUBITAK) [118E214, 118E215]en_US
dc.description.sponsorshipThis research is supported by the Turkish Scientific and Technical Research Council (TUBITAK) , with Project No: 118E214 and Project No: 118E215.en_US
dc.identifier.doi10.1016/j.jestch.2020.08.008
dc.identifier.endpage298en_US
dc.identifier.issn2215-0986
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85090113797en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage284en_US
dc.identifier.urihttps://doi.org/10.1016/j.jestch.2020.08.008
dc.identifier.urihttps://hdl.handle.net/20.500.14619/4901
dc.identifier.volume24en_US
dc.identifier.wosWOS:000631845100002en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier - Division Reed Elsevier India Pvt Ltden_US
dc.relation.ispartofEngineering Science and Technology-An International Journal-Jestechen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectSocial navigationen_US
dc.subjectHuman-aware navigationen_US
dc.subjectHuman-robot interactionen_US
dc.subjectSocial roboticsen_US
dc.subjectMobile robotsen_US
dc.subjectROSen_US
dc.titleSocial navigation framework for assistive robots in human inhabited unknown environmentsen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu