Simultaneous object recognition and position tracking for robotic applications

Aristos, D; Tzafestas, S

dc.contributor.author	Aristos, D	en
dc.contributor.author	Tzafestas, S	en
dc.date.accessioned	2014-03-01T02:46:31Z
dc.date.available	2014-03-01T02:46:31Z
dc.date.issued	2009	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32693
dc.subject	3D reconstruction	en
dc.subject	Camera calibration	en
dc.subject	Hand/eye calibration	en
dc.subject	Triangulation-based laser sensor	en
dc.subject.other	2D images	en
dc.subject.other	3-D space	en
dc.subject.other	3D reconstruction	en
dc.subject.other	CAD data	en
dc.subject.other	Camera calibration	en
dc.subject.other	Hand/eye calibration	en
dc.subject.other	Image processing algorithm	en
dc.subject.other	Machine vision	en
dc.subject.other	Position tracking	en
dc.subject.other	Rigid objects	en
dc.subject.other	Robot's workspace	en
dc.subject.other	Robotic applications	en
dc.subject.other	Specific sensors	en
dc.subject.other	Triangulation-based laser sensor	en
dc.subject.other	Calibration	en
dc.subject.other	Cameras	en
dc.subject.other	Computer vision	en
dc.subject.other	Image reconstruction	en
dc.subject.other	Industrial robots	en
dc.subject.other	Mechatronics	en
dc.subject.other	Repair	en
dc.subject.other	Robotics	en
dc.subject.other	Sensors	en
dc.subject.other	Surface reconstruction	en
dc.subject.other	Three dimensional	en
dc.subject.other	Tracking (position)	en
dc.subject.other	Triangulation	en
dc.subject.other	Two dimensional	en
dc.subject.other	Object recognition	en
dc.title	Simultaneous object recognition and position tracking for robotic applications	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICMECH.2009.4957198	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICMECH.2009.4957198	en
heal.identifier.secondary	4957198	en
heal.publicationDate	2009	en
heal.abstract	Object recognition techniques are well known in the field of machine vision, and aim at the classification of certain observed rigid objects based on the information acquired by a specific sensor. These techniques can either be performed in the 2D image space by simply applying suitable image processing algorithms, or in the real world 3D space by performing surface reconstruction of the object's surface and comparing it with a database of known CAD data. This paper presents a combination of techniques which not only recognize and categorize the observed rigid objects but also compute their 3D pose (position and orientation) with respect an industrial robot's workspace frame. This task is very useful in the field of robotics as it allows an industrial robot to simultaneously recognize and follow the displacements of a specific rigid object, among other objects that may co-exist in the same environment. © 2009 IEEE.	en
heal.journalName	IEEE 2009 International Conference on Mechatronics, ICM 2009	en
dc.identifier.doi	10.1109/ICMECH.2009.4957198	en