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Analog-digital hybrid computing with SnS2 memtransistor for low-powered sensor fusion.


ABSTRACT: Algorithms for intelligent drone flights based on sensor fusion are usually implemented using conventional digital computing platforms. However, alternative energy-efficient computing platforms are required for robust flight control in a variety of environments to reduce the burden on both the battery and computing power. In this study, we demonstrated an analog-digital hybrid computing platform based on SnS2 memtransistors for low-power sensor fusion in drones. The analog Kalman filter circuit with memtransistors facilitates noise removal to accurately estimate the rotation of the drone by combining sensing data from the gyroscope and accelerometer. We experimentally verified that the power consumption of our hybrid computing-based Kalman filter is only 1/4th of that of the traditional software-based Kalman filter.

SUBMITTER: Rehman S 

PROVIDER: S-EPMC9119935 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Analog-digital hybrid computing with SnS<sub>2</sub> memtransistor for low-powered sensor fusion.

Rehman Shania S   Khan Muhammad Farooq MF   Kim Hee-Dong HD   Kim Sungho S  

Nature communications 20220519 1


Algorithms for intelligent drone flights based on sensor fusion are usually implemented using conventional digital computing platforms. However, alternative energy-efficient computing platforms are required for robust flight control in a variety of environments to reduce the burden on both the battery and computing power. In this study, we demonstrated an analog-digital hybrid computing platform based on SnS<sub>2</sub> memtransistors for low-power sensor fusion in drones. The analog Kalman filt  ...[more]

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