Optimal mobile robot pose estimation using geometrical maps

Author

Borges, Geovany Araujo ; Aldon, Marie-José

Author_Institution

Robotics Dept., CNRS, Montpellier, France

Volume

Issue

fYear

2002

fDate

2/1/2002 12:00:00 AM

Firstpage

Lastpage

Abstract

We propose a weighted least-squares (WLS) algorithm for optimal pose estimation of mobile robots using geometrical maps as environment models. Pose estimation is achieved from feature correspondences in a nonlinear framework without linearization. The proposed WLS approach yields optimal estimates in the least-squares sense, is applicable to heterogeneous geometrical features decomposed in points and lines, and has an O(N) computation time

Keywords

Kalman filters; computational complexity; covariance matrices; geometry; least squares approximations; mobile robots; path planning; environment models; geometrical maps; heterogeneous geometrical features; mobile robot; nonlinear framework; optimal pose estimation; weighted least-squares algorithm; Actuators; Automatic control; Gears; Kinematics; Mechanical factors; Mobile robots; Optimal control; Robotics and automation; Vehicles; Wheels;

fLanguage

English

Journal_Title

Robotics and Automation, IEEE Transactions on

Publisher

ieee

ISSN

1042-296X

Type

jour

DOI

10.1109/70.988978

Filename

988978

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1258637