2024
DOI: 10.21203/rs.3.rs-3412454/v1
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Payload Prediction for Quadro Drone using Temporal Deep Machine Learning Models

Raed Abu Zitar,
Mariam Kashkash,
Amal El Fallah Seghrouchni
et al.

Abstract: In this paper, four different deep-learning and temporal machine-learning techniques are used to predict the payload of the DJI Matrice 100 quadcopter drone based on its tracking data. Tracking variables for real-life experimentations are provided as open source for payloads of 0.0, 250, 500, and 750 grams. The drone is a Quado drone DJI matrice 100. The Machine Learning techniques are RNN, LSTM, TCN, and GRU. The values of the tracks’ kinematics come from several different flights for the different loads. The… Show more

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