Robot localization in nonsmooth environments: experiments with a new filtering technique

Author

Antoniali, Fabio M. ; Oriolo, Giuseppe

Author_Institution

Dipartimento di Inf. e Sistemistica, Rome Univ., Italy

Volume

2

fYear

2001

fDate

2001

Firstpage

1591

Abstract

Considers the localization problem for a unicycle robot equipped with range finders and moving in environments with nonsmooth geometry, i.e., whose obstacle-free region, has a piecewise-linear boundary. Using the multi-hypothesis density filter, a multi-modal estimator based on the Bayesian framework, an innovative localization system is devised and implemented on the ATRV-Jr robot. Experiments illustrate the superior performance of the new filter with respect to the classical extended Kalman filter.

Keywords

Monte Carlo methods; discrete time systems; distance measurement; filtering theory; mean square error methods; mobile robots; probability; robot kinematics; state estimation; stochastic systems; ATRV-Jr robot; Bayesian framework; classical extended Kalman filter; multi-hypothesis density filter; multi-modal estimator; nonsmooth environments; nonsmooth geometry; obstacle-free region; piecewise-linear boundary; range finders; robot localization; unicycle robot; Filtering; Filters; Integrated circuit modeling; Integrated circuit noise; Mobile robots; Noise measurement; Piecewise linear techniques; Random variables; Robot localization; Robot sensing systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Automation, 2001. Proceedings 2001 ICRA. IEEE International Conference on

ISSN

1050-4729

Print_ISBN

0-7803-6576-3

Type

conf

DOI

10.1109/ROBOT.2001.932838

Filename

932838