Rao, N and Sundaram, S and Raghavendra, V (2023) Computationally Light Spectrally Normalized Memory Neuron Network based Estimator for GPS-denied operation of Micro-UAV. In: UNSPECIFIED, pp. 1894-1899.
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Abstract
This paper addresses the problem of position estimation in UAVs operating in a cluttered environment where GPS information is unavailable. A learning-based approach is proposed that takes in the rotor RPMs and past state as input and predicts the one-step-ahead position of the UAV using a novel spectral-normalized memory neural network (SN-MNN). The spectral normalization guarantees stable and reliable prediction performance. The predicted position is transformed to the global coordinate frame (GPS), which is then fused along with the odometry of other peripheral sensors like IMU, barometer, compass, etc., using the onboard extended Kalman filter (EKF) to estimate the states of the UAV. The experimental flight data collected from an RTK-GPS facility using a micro-UAV is used to train the SN-MNN. The PX4-ECL library is used to fuse the predicted data using the SN-MNN, and the estimated position is compared with actual ground truth data. The proposed algorithm doesn't require any additional onboard sensors and is computationally light. The performance of the proposed approach is compared with the current state-of-art GPS-denied algorithms, and it can be seen that the proposed algorithm has the least RMSE for position estimates. © 2023 IEEE.
Item Type: | Conference Paper |
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Publication: | 9th 2023 International Conference on Control, Decision and Information Technologies, CoDIT 2023 |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Additional Information: | The copyright for this article belongs to author. |
Keywords: | Extended Kalman filters; Neural networks; Unmanned aerial vehicles (UAV), Cluttered environments; Learning-based approach; Memory neuron networks; Micro UAVs; Micro-UAV; Network-based; Neural-networks; Position estimation; Prediction performance; Spectral normalization, Global positioning system |
Department/Centre: | Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering) |
Date Deposited: | 04 Mar 2024 09:26 |
Last Modified: | 04 Mar 2024 09:26 |
URI: | https://eprints.iisc.ac.in/id/eprint/84292 |
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