Multi-Robot Visual Navigation Structure based on Lukas-Kanade Algorithm

dc.contributor.authorELASRI, Abdelfattah
dc.contributor.authorCHERROUN, Lakhmissi
dc.contributor.authorNADOUR, Mohamed
dc.date.accessioned2022-04-14T10:25:17Z
dc.date.available2022-04-14T10:25:17Z
dc.date.issued2022-01-24
dc.descriptionForum Intervention of Artificial Intelligence and Its Applications. Faculty of Exat science. University of Eloueden_US
dc.description.abstractThis paper presents an efficient control structure of two mobile robots based-visual navigation methods in an indoor environment. The proposed navigators are based on decision systems employed the necessary values estimated by a Lukas-Kanade (LK) algorithm of optical flow (OF) approach. The robots control systems use the generated motion values in order to detect and estimate the positions of the nearest obstacles and objects around each mobile robot. The multi-robot system task is to navigate autonomously in their environment safely without collisions. Obstacles are identified and detected with the employed cameras of each robot based on video acquisition and image processing steps. The efficiency of the proposed approach is verified in simulation using Visual Reality Toolbox. Simulation results demonstrate that the visual based control system allows autonomous navigation without any collision with obstacles..en_US
dc.identifier.citationELASRI, Abdelfattah • CHERROUN, Lakhmissi. NADOUR, Mohamed. Multi-Robot Visual Navigation Structure based on Lukas-Kanade Algorithm. Forum of Artificial Intelligence and Its Applications. 24-26 Jan 2022. Faculty of Exat science. University of Eloued. [visited in ../../….]. available from [copy the link here]en_US
dc.identifier.urihttp://dspace.univ-eloued.dz/handle/123456789/10822
dc.language.isoenen_US
dc.publisherUniversity of Eloued جامعة الواديen_US
dc.subjectLukas-Kanade algorithm · Multi-Robot · Visual · Camera · Decision · VRML toolboxen_US
dc.titleMulti-Robot Visual Navigation Structure based on Lukas-Kanade Algorithmen_US
dc.typeOtheren_US

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