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Open Vision System for Low-Cost Robotics Education

dc.contributor.authorVega, Julio
dc.contributor.authorCañas, José M.
dc.date.accessioned2024-01-31T15:49:22Z
dc.date.available2024-01-31T15:49:22Z
dc.date.issued2019-11-06
dc.identifier.citationOpen vision system for low-cost Robotics education. Electronics, 8:1295--1315, November 2019es
dc.identifier.issn2079-9292
dc.identifier.urihttps://hdl.handle.net/10115/29368
dc.description.abstractVision devices are currently one of the most widely used sensory elements in robots: commercial autonomous cars and vacuum cleaners, for example, have cameras. These vision devices can provide a great amount of information about robot surroundings. However, platforms for robotics education usually lack such devices, mainly because of the computing limitations of low cost processors. New educational platforms using Raspberry Pi are able to overcome this limitation while keeping costs low, but extracting information from the raw images is complex for children. This paper presents an open source vision system that simplifies the use of cameras in robotics education. It includes functions for the visual detection of complex objects and a visual memory that computes obstacle distances beyond the small field of view of regular cameras. The system was experimentally validated using the PiCam camera mounted on a pan unit on a Raspberry Pi-based robot. The performance and accuracy of the proposed vision system was studied and then used to solve two visual educational exercises: safe visual navigation with obstacle avoidance and person-following behavior.
dc.language.isoenges
dc.publisherMDPIes
dc.rightsAttribution 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleOpen Vision System for Low-Cost Robotics Educationes
dc.typeinfo:eu-repo/semantics/articlees
dc.identifier.doi10.3390/electronics8111295es
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses


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Attribution 4.0 InternacionalExcept where otherwise noted, this item's license is described as Attribution 4.0 Internacional