A laser scanner based mobile robust SLAM algorithm with improved convergence properties

Lionis, GS; Kyriakopoulos, KJ

dc.contributor.author	Lionis, GS	en
dc.contributor.author	Kyriakopoulos, KJ	en
dc.date.accessioned	2014-03-01T02:42:03Z
dc.date.available	2014-03-01T02:42:03Z
dc.date.issued	2002	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30746
dc.subject	extended kalman filter	en
dc.subject	Laser Scanner	en
dc.subject	Mobile Robot	en
dc.subject	Simultaneous Localization and Map Building	en
dc.subject.other	Algorithms	en
dc.subject.other	Collision avoidance	en
dc.subject.other	Feature extraction	en
dc.subject.other	Geometry	en
dc.subject.other	Kalman filtering	en
dc.subject.other	Motion estimation	en
dc.subject.other	Extended Kalman filters	en
dc.subject.other	Laser scanner	en
dc.subject.other	Simulataneous localization and map building	en
dc.subject.other	Mobile robots	en
dc.title	A laser scanner based mobile robust SLAM algorithm with improved convergence properties	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/IRDS.2002.1041453	en
heal.identifier.secondary	http://dx.doi.org/10.1109/IRDS.2002.1041453	en
heal.publicationDate	2002	en
heal.abstract	We have developed a laser scanner based simultaneous localization and map building method, specifically addressing the divergence problem of the classical Extended Kalman Filters (EKF) based Simultaneous Localization and Map Building (SLAM) algorithms. Our method utilizes two EKFs. The first is used to estimate the orientations of the MR and the obstacles, and the second estimates the positions of the MR and of the obstacles. Experimental results are also presented to verify our arguments.	en
heal.journalName	IEEE International Conference on Intelligent Robots and Systems	en
dc.identifier.doi	10.1109/IRDS.2002.1041453	en
dc.identifier.volume	1	en
dc.identifier.spage	582	en
dc.identifier.epage	587	en