Motion-adaptive Kalman filter duty-cycling

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In this research, we present a motion-adaptive duty-cycling approach to estimate orientation using inertial sensors.
We investigated how a proportional forward-controller could be used to adjust the duty-cycle of inertial sensing
units (IMU) and the orientation estimation update rate of an extended Kalman filter (EKF).

Block diagram of the motion-adaptive EKF design. The orientation estimation rate is controlled via angular rate measurements obtained from the gyroscopes. The control operation is illustrated as a mapping function that produces the duty-cycle rate D. This illustration was adapted from the fixed rate EKF design.








As an input for the forward-controller, we used the sensitive gyroscope, which responds quickly to rotational motion.

Illustration of the proportional controller gain mapping. The controller input d was derived from the angular rate measurements. Dashed lines indicate the controller gain sweep used subsequently to analyse the performance of our motion-adaptive duty-cycling approach.

















In sample data recordings and a simulated daily life dataset from a wrist-worn IMU, we showed that our motion-adaptive approach incurs substantially lower errors that a static duty-cycling approach. During phases with low or no rotation motion, as it is often occurring in daily activities, our approach can dynamically reduce the IMU operation to 20% of the regular rate. Results showed that duty-cycles of 50% are common during low-wrist rotation activities, such as reading and typing, while orientation error is below 1°.
This research is an initial step towards power-efficient algorithms which could increase the recording duration of IMUs when orientation estimates need to be calculated in real-time on the sensor node.

Work with us

For this project, we aim to investigate different controller-strategies and their effects on the orientation estimation. Additional sensor-fusion algorithms for the orientation estimation using different orientation representation could be investigated.



Adrian Derungs, Han Lin, Holger Harms, Oliver Amft, "Motion-adaptive duty-cycling to estimate orientation using inertial sensors", Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops, IEEE, 2014.


Adrian Derungs

Friedrich-Alexander-Universität Erlangen-Nürnberg