Calibration and On-line Data Selection of Multiple Optical Flow Sensors for Mobile Robot Localization

Abstract

This paper proposes a calibration method as well as a computational algorithm to integrate the data of multiple optical flow sensors for 2-dimensional trajectory measurement. 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 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. Experimental results are presented to support the proposed methods.