Extrinsic Calibration of Multiple Inertial Sensors From Arbitrary Trajectories

Abstract

This paper addresses the problem of choosing a sparse subset of measurements for quick calibration parameter estimation. A standard solution to this is selecting a measurement only if its utility-the difference between posterior (with the measurement) and prior information (without the measurement)-exceeds some threshold. Theoretically, utility, a function of the parameter estimate, should be evaluated at the estimate obtained with all measurements selected so far, hence necessitating a recalibration with each new measurement. However, we hypothesize that utility is insensitive to changes in the parameter estimate for many systems of interest, suggesting that evaluating utility at some initial parameter guess would yield equivalent results in practice. We provide evidence supporting this hypothesis for extrinsic calibration of multiple inertial measurement units (IMUs), showing the reduction in calibration time by two orders of magnitude by forgoing recalibration for each measurement.

Near Real-Time Volumetric Estimates Using Unmanned Aerial Platforms Equipped with Depth and Tracking Sensors

“…The pose between two consecutive movements is held for a few seconds before moving the platform to another position. In such a way, a stable signal is produced with sharp acceleration peaks along a well-defined direction [ 21 ].…”