Calibration and on-line data selection of multiple optical flow sensors for odometry applications

This work proposes a calibration method and a computational algorithm to integrate the data of multiple optical flow sensors for two-dimensional trajectory measurements. Optical flow sensors offer a different kind of odometer as compared to the wheel encoder. Using multiple sensors can reduce the effect of measurement uncertainties. Since all sensors are mounted on a rigid body, their measurement data must obey a certain relation, which is utilized in this work. Additionally, mathematical formulae are developed to realize the computation. Analytical results show that the calibration procedure can be cast as an optimization problem given measurement data. Furthermore, the rigid-body relation is formulated as a null-space constraint using the calibrated parameters. Unreliable sensor measurements can be removed during operation by accessing the error distance to the null space. Experimental results are presented to support the proposed methods.