Stochastic self localization of a mobile robot

dc.contributor.author	Dharmapriya, USS
dc.contributor.author	Dileepa, R
dc.contributor.author	Dharmawardena, HI
dc.contributor.author	Dharmadasa, YC
dc.contributor.author	Pathirana, C
dc.date.accessioned	2013-10-21T02:12:47Z
dc.date.available	2013-10-21T02:12:47Z
dc.date.issued	2010
dc.identifier.uri	http://dl.lib.mrt.ac.lk/handle/123/8212
dc.description.abstract	This paper describes a solution to the localization problem based on the Extended Kalman filter Estimation of the location and path of a Nonholonomic robot in a given environment is a key problem which needs to be overcame for successful mobile robot navigation. In this work a differential drive vehicle model is used and evolution of the vehicle motion is modeled using vehicle frame translation derived from successive dead reckoned poses as a control input. The nearest neighbor algorithm is used for the purpose of data association .The localization algorithm is simulated using matlab. The results shown that the proposed approach localizes the robot with the necessary accuracy.
dc.language	en
dc.title	Stochastic self localization of a mobile robot
dc.type	Conference-Extended-Abstract
dc.identifier.year	2010
dc.identifier.conference	Research for Industry
dc.identifier.place	Faculty of Engineering, University of Moratuwa
dc.identifier.pgnos	pp. 128-130
dc.identifier.proceeding	16th Annual symposium on Research and Industry