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Body sensor calibration and construction of 3D maps for robot navigation using the framework of conformal geometric algebra

Published online by Cambridge University Press:  01 July 2008

C. López-Franco  and
E. Bayro-Corrochano
C. López-Franco
Affiliation:
CINVESTAV Unidad Guadalajara, Department of Electrical Engineering and Computer Science, Guadalajara, Jalisco, México
E. Bayro-Corrochano*
Affiliation:
CINVESTAV Unidad Guadalajara, Department of Electrical Engineering and Computer Science, Guadalajara, Jalisco, México
*
*Corresponding author. E-mail: bayro@ira.uka.de
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Summary

The research, described in this paper, concerns the robot indoor navigation, emphasizing the aspects of sensor model and calibration, environment representation, and self-localization. The main point is that combining all of these aspects, an effective navigation system is obtained. We present a model of the catadioptric image formation process. Our model simplifies the operations needed in the catadioptric image process. Once we know the model of the catadioptric sensor, we have to calibrate it with respect to the other sensors of the robot, in order to be able to fuse their information. When the sensors are mounted on a robot arm, we can use the hand-eye calibration algorithm to calibrate them. In our case the sensors are mounted on a mobile robot that moves over a flat floor, thus the sensors have less degrees of freedom. For this reason we develop a calibration algorithm for sensors mounted on a mobile robot. Finally, combining all the previous results and a scan matching algorithm that we develop, we build 3D maps of the environment. These maps are used for the self-localization of the robot and to carry out path following tasks. In this work we present experiments which show the effectiveness of the proposed algorithms.

Keywords

Geometric algebraConformal geometric algebraCatadioptric systemsScan matchingOmnidirectional vision
Type
Article
Information
Robotica , Volume 26 , Special Issue 4: Geometry in Robotics: Sensing , July 2008 , pp. 465 - 481
Copyright
Copyright © Cambridge University Press 2008

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