JOURNAL ARTICLE

Calibration and Data Integration of Multiple Optical Flow Sensors for Mobile Robot Localization

Abstract

This paper proposes a calibration method as well as a computational algorithm to integrate multiple optical flow sensors. Optical flow sensors offer a different kind of odometer as compared with the wheel encoder. Using multiple sensors, it is possible to reduce the effect of measurement uncertainties. Since all sensors are mounted on a rigid body, their measurement data must obey a certain relation. This relation is utilized in this paper and mathematical formulations are developed to realize the computation. It is shown that the calibration procedure can be cast as an optimization problem given enough measurement data. Further, the rigid-body relation is formulated as a null-space constraint using the calibrated parameters. During operation, unreliable sensor measurements can be removed by accessing the error distance to the null space. Simulation results are presented to support the proposed methods.

Keywords:
Odometer Calibration Null (SQL) Relation (database) Computer science Constraint (computer-aided design) Encoder Mobile robot Computation Flow (mathematics) Algorithm Robot Computer vision Artificial intelligence Mathematics Data mining

Metrics

3
Cited By
1.58
FWCI (Field Weighted Citation Impact)
12
Refs
0.87
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Control and Dynamics of Mobile Robots
Physical Sciences →  Engineering →  Control and Systems Engineering
Indoor and Outdoor Localization Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Robotic Path Planning Algorithms
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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