NDLI: A single landmark based localization algorithm for non-holonomic mobile robots

Content Provider	IEEE Xplore Digital Library
Author	Sert, H. Kokosy, A. Perruquetti, W.
Copyright Year	2011
Description	Author affiliation: ALIEN INRIA - LNE, Parc Scientifique de la Haute Borne 40, avenue Halley Bt.A, Park Plaza 59650 Villeneuve d'Ascq and LAGIS FRE CNRS 3303, Ecole Centrale de Lille, BP 48, Cité Scientifique, 59651 Villeneuve-d'Ascq, France (Perruquetti, W.) \|\| ISEN and LAGIS FRE CNRS 3303, 41 bvd Vauban, 59 046 Lille Cedex, France (Sert, H.; Kokosy, A.)
Abstract	This paper proposes a single landmark based localization algorithm for non-holonomic mobile robots. In the case of a unicycle robot model, the localization problem is equivalent to the system observability. Based on this observation, the proposed localization method consists in finding a vector function which depends on the measurement vector and its derivatives. In order to compute estimates of the successive derivatives of the measurement vector, we will use a numerical differentiation method. When the robot is able to only measure the relative angle between itself and the landmark in 2D case, the algorithm estimates the posture of the robot, under the hypothesis that control inputs are known. But, sometimes it is also useful to be able to estimate the control input (for example when the robot slips). This is possible with the proposed algorithm by using a landmark in dimension three. The simulation results will be given in order to show the effectiveness of the proposed algorithm. Moreover, these results are compared with those obtained by an Extended Kalman Filter in order to underline the advantages of the new algorithm.
Starting Page	293
Ending Page	298
File Size	233350
Page Count	6
File Format	PDF
ISBN	9781612843865
ISSN	10504729
e-ISBN	9781612843858
DOI	10.1109/ICRA.2011.5980002
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robot kinematics Equations Mathematical model Noise Estimation Noise measurement
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

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