Localization for multi-axle train configured CFMMRs

Author

Vogt, Andrew ; Minor, Mark

Author_Institution

Dept. of Mech. Eng., Univ. of Utah, Salt Lake City, UT, USA

fYear

2009

fDate

10-15 Oct. 2009

Firstpage

5567

Lastpage

5572

Abstract

This paper presents a data fusion structure based on comparing geometric configurations of serial connected multi-axle compliant framed robots. Data sources include global odometry derived sources and a novel strain-measurement based relative posture sensor (RPS). Geometric methods are used because stochastic data fusion, developed from prior research, was erroneous when applied to more generalized multi-axle configurations. Our results show an excellent response predicting expected configurations and a reasonable response with un-expected configurations.

Keywords

geometry; mobile robots; sensor fusion; strain measurement; compliant framed wheeled modular mobile robots; geometric configurations; multi axle train configured CFMMRs; serial connected multi-axle compliant framed robots; stochastic data fusion structure; strain-measurement based relative posture sensor; Axles; Control systems; Intelligent robots; Kinematics; Mobile robots; Motion control; Robot sensing systems; Sensor fusion; Signal processing algorithms; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on

Conference_Location

St. Louis, MO

Print_ISBN

978-1-4244-3803-7

Electronic_ISBN

978-1-4244-3804-4

Type

conf

DOI

10.1109/IROS.2009.5354125

Filename

5354125