Model-Free Unsupervised Anomaly Detection of a General Robotic System Using a Stacked LSTM and Its Application to a Fixed-Wing Unmanned Aerial Vehicle
Author:
Affiliation:
1. School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST),Daejeon,South Korea,34141
Funder
Defense Acquisition Program Administration
Agency for Defense Development
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9981026/9981028/09981950.pdf?arnumber=9981950
Reference36 articles.
1. UAV Quadrotor Fault Detection and Isolation Using Artificial Neural Network and Hammerstein-Wiener Model
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3. Anomaly Detection of Fixed-Wing Unmanned Aerial Vehicle (UAV) Based on Cross-Feature-Attention LSTM Network;Communications in Computer and Information Science;2023-11-26
4. Unsupervised Anomaly Detection of Unmanned Aerial Vehicles based on Spatial-Temporal Model with Flight Data;2023 6th International Conference on Intelligent Autonomous Systems (ICoIAS);2023-09-22
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