Double Exponential Smoothing for predictive vision based target tracking of a wheeled mobile robot

Author

Guerin, Francois ; Fabri, Simon G. ; Bugeja, Marvin K.

Author_Institution

Res. Group in Electrotechnics & Automatics (GREAH), Univ. of Le Havre, Le Havre, France

fYear

2013

fDate

10-13 Dec. 2013

Firstpage

3535

Lastpage

3540

Abstract

This paper describes the design of a novel nonlinear kinematic controller which allows a wheeled mobile robot to track a moving target at a given separation distance. The Double Exponential Smoothing algorithm is employed to deal with uncertainties in the measurements and to acquire a predictive estimate for the robot´s relative position. This estimate is used to automatically adjust the proportional gain of the controller in order to regulate the tracking error.

Keywords

mobile robots; nonlinear control systems; object tracking; robot kinematics; robot vision; smoothing methods; wheels; controller proportional gain; double exponential smoothing; measurement uncertainties; nonlinear kinematic controller; predictive vision based target tracking; robot relative position predictive estimation; tracking error regulation; wheeled mobile robot; Algorithm design and analysis; Machine vision; Mobile robots; Prediction algorithms; Smoothing methods; Target tracking; Trajectory;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on

Conference_Location

Firenze

ISSN

0743-1546

Print_ISBN

978-1-4673-5714-2

Type

conf

DOI

10.1109/CDC.2013.6760426

Filename

6760426