An Algorithm for Rigid-body Angular Velocity and Attitude Estimation Based on Isotropic Accelerometer Strapdowns

[+] Author and Article Information
Ting Zou

Postdoctoral Fellow, Department of Mechanical Engineering and Centre for Intelligent Machines, McGill University, Montréal, Canada

Jorge Angeles

Professor, Fellow of ASME, Department of Mechanical Engineering and Centre for Intelligent Machines, McGill University, Montréal, Canada

1Corresponding author.

ASME doi:10.1115/1.4039435 History: Received July 12, 2017; Revised February 21, 2018


A novel algorithm for the estimation of rigid-body angular velocity and attitude---the most challenging part of pose-and-twist estimation---based on isotropic accelerometer strapdowns, is proposed in this paper. Quaternions, which employ four parameters for attitude representation, provide a compact description without the drawbacks brought about by other representations, for example, the gimbal lock of Euler angles. Within the framework of quaternions for rigid-body angular velocity and attitude estimation, the proposed methodology automatically preserves the unit norm of the quaternion, thus improving the accuracy and efficiency of the estimation. By virtue of the inherent nature of isotropic accelerometer strapdowns, the centripetal acceleration is filtered out, leaving only its tangential counterpart, to be estimated and updated. Meanwhile, using the proposed integration algorithm, the angular velocity and the quaternion, which are dependent only on the tangential acceleration, are calculated and updated at appropriate sampled instants for high accuracy. This strategy, which brings about robustness, allows for relatively large time step sizes, low memory demands and low computational complexity. The proposed algorithm is tested by simulation examples of the angular velocity and attitude estimation of a free-rotating brick and the end-effector of an industrial robot. The simulation results showcase the algorithm with low errors, as estimated based on energy conservation, and high-order rate of convergence, as compared with other algorithms in the literature.

Copyright (c) 2018 by ASME
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