A novel Redundant Inertial Measurement Unit and error compensation technology

He, Kaifei; Shao, Yuping; Wang, Xiaoxue; Wang, Chenyang

doi:10.1201/b18284-28

Cited by 2 publications

(2 citation statements)

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“…To realize these benefits, accurate extrinsic calibration is crucial to determine the relative pose of each IMU to others. Various extrinsic calibration methods for multi-IMU systems have been developed, including those utilizing prescribed trajectories [7][8][9] and aiding sensors like cameras [10]. Notably, self-calibration methods [11][12][13], which rely solely on IMU measurements themselves, offer significant benefits, especially in scenarios requiring recalibration due to intentional or unintentional changes in sensor configuration during robot operation, such as part loosening or thermal expansion.…”

Section: Introductionmentioning

confidence: 99%

Extrinsic Calibration of Multiple Inertial Sensors From Arbitrary Trajectories

Lee

Hanley

2022

IEEE Robot. Autom. Lett.

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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.

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Section: Introductionmentioning

confidence: 99%

Extrinsic Calibration of Multiple Inertial Sensors From Arbitrary Trajectories

Lee

Hanley

2022

IEEE Robot. Autom. Lett.

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“…Cho and Park [10] divided the calibration scheme into two parts: the static multi-position procedure and the angular motion procedure, and the estimation algorithm was proposed based on the least square method. He et al [11] designed the similar scheme as [10], but the accelerometer measurement data was only collected at the static state. Jafari et al [12] presented two calibration algorithms based on Kalman filter and least square method respectively, that the Kalman filter based method was used in three-stage dynamic procedure and the least square based method was used in the static multi-position procedure.…”

Section: Introductionmentioning

confidence: 99%

The calibration method for accelerometers in the redundant MEMS inertial navigation system

Shi

Ding

et al. 2021

Meas. Sci. Technol.

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Compared with the non-redundant inertial navigation system (INS), the redundant INS (RINS) has more error parameters and the system is more complicated. The calibration methods for non-redundant INS are unable to be adopted by RINS directly. Meanwhile, the inner lever arm effect of accelerometers is more severe in RINS, which is not supposed to be ignored in the error compensation. To solve the problems above, this paper proposes a novel calibration method for accelerometers in RINS. First, the paper analyses and models the bias, scale factor error, installation angle error and lever arm error. Based on the error model, two Kalman filters are designed to estimate the error parameters. The calibration is divided into two steps: the bias, scale factor error and installation angle error are calibrated by the static multi-position experiment first, and then the lever arm error is calibrated by the rotation experiment. Experiments prove that the proposed method can effectively calibrate the deterministic error of the accelerometers, that the estimation errors are controlled at 1 × 10 −4 level. Further, the paper studies and optimizes the turntable rotation scheme in the lever arm error calibration experiment, and proposes the design principles for the rotation scheme. Comparing with the casually designed scheme, the optimized procedure can improve the accuracy by almost an order of magnitude as well as the time-consumption being shortened by 40%. The design principles are applicable to the other inertial navigation systems to improve the calibration accuracy and reduces the time cost.

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A novel Redundant Inertial Measurement Unit and error compensation technology

Cited by 2 publications

References 0 publications

Extrinsic Calibration of Multiple Inertial Sensors From Arbitrary Trajectories

Extrinsic Calibration of Multiple Inertial Sensors From Arbitrary Trajectories

The calibration method for accelerometers in the redundant MEMS inertial navigation system

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