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dc.contributor.authorGandarias, Juan Manuel
dc.contributor.authorGómez-de-Gabriel, Jesús Manuel 
dc.contributor.authorPastor-Martín, Francisco
dc.contributor.authorMuñoz-Ramirez, Antonio Jose 
dc.date.accessioned2019-09-11T10:21:19Z
dc.date.available2019-09-11T10:21:19Z
dc.date.created2019
dc.date.issued2019-09-11
dc.identifier.urihttps://hdl.handle.net/10630/18303
dc.description.abstractA method for the estimation of the roll angle of a human forearm, when grasped by a robot with an underactuated gripper, using proprioceptive information only, is being developed. Knowing the angle around the forearm's axis (i.e. roll angle) is key for the safe manipulation of the human limb and biomedical sensor placement among others. The adaptive gripper has two independent underactuated fingers with two phalanges and a single actuator each. The final joint position of the gripper provides information related to the shape of the grasped object without the need for external contact or force sensors. Regression methods to estimate the roll angle of the grasping have been trained with forearm grasping information from different humans at each angular position. The results show that it is possible to accurately estimate the rolling angle of the human arm, not only for known people but also for humans for which haven't been previously trained.en_US
dc.description.sponsorshipUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Beca European Commission under grant agreement BES-2016-078237en_US
dc.language.isoengen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectRobóticaen_US
dc.subject.otherKinesthetic perceptionen_US
dc.subject.otherroboticsen_US
dc.titleHuman-Arm Roll Estimation in Underactuated Grippers with Proprioceptive Feedbacken_US
dc.typeinfo:eu-repo/semantics/workingPaperen_US
dc.centroEscuela de Ingenierías Industrialesen_US
dc.relation.eventtitleWorld Haptics Conferenceen_US
dc.relation.eventplaceTokio (Japón)en_US
dc.relation.eventdate07/2019en_US


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