Fusing range and intensity images for mobile robot localization

Author

Neira, Jose ; Tardos, Juan D. ; Horn, Joachim ; Schmidt, Gunther

Author_Institution

Dept. de Inf. e Ingenieria de Sistemas, Zaragoza Univ., Spain

Volume

15

Issue

1

fYear

1999

fDate

2/1/1999 12:00:00 AM

Firstpage

76

Lastpage

84

Abstract

We present the two-dimensional (2-D) version of the symmetries and perturbation model (SPmodel), a probabilistic representation model and an extended Kalman filter integration mechanism for uncertain geometric information that is suitable for sensor fusion and integration in multisensor systems. We apply the SPmodel to the problem of location estimation in indoor mobile robotics, experimenting with the mobile robot MACROBE. We have chosen two types of complementary sensory information: (1) range images; (2) intensity images; obtained from a laser sensor. Results of these experiments show that fusing simple and computationally inexpensive sensory information can allow a mobile robot to precisely locate itself. They also demonstrate the generality of the proposed fusion and integration mechanism

Keywords

Kalman filters; feature extraction; laser ranging; mobile robots; nonlinear filters; probability; sensor fusion; stereo image processing; MACROBE mobile robot; SPmodel; extended Kalman filter integration mechanism; indoor mobile robotics; intensity images; laser sensor; location estimation; mobile robot localization; multisensor systems; probabilistic representation model; range images; symmetries and perturbation model; uncertain geometric information; Infrared sensors; Machine vision; Mobile robots; Robot sensing systems; Robustness; Sensor fusion; Sensor systems; Solid modeling; Two dimensional displays; Uncertainty;

fLanguage

English

Journal_Title

Robotics and Automation, IEEE Transactions on

Publisher

ieee

ISSN

1042-296X

Type

jour

DOI

10.1109/70.744604

Filename

744604