Data-driven model enables early, high-accuracy intention recognition in UAV swarms (IMAGE)
Caption
Unmanned Aerial Vehicle (UAV) intention recognition has been extensively studied. However, when it comes to a UAV swarm problem, their intention recognition study was left blank. The flowchart demonstrates the framework of the intention recognition method proposed in this research. To describe the UAV swarm's basic motions, the behaviors of a UAV swarm are classified into contraction, free movement, and expansion. Once the data are collected from UAVs and stored in an array, an Artificial Neural Network (ANN) can detect the motion and analyze the probabilities of contraction, free movement, or expansion motion.
Credit
Zhichao Wang, Jiayun Chen, Jiaju Wang, Qiang Shen.
Usage Restrictions
Credit must be given to the creator. Only noncommercial uses of the work are permitted. No derivatives or adaptations of the work are permitted.
License
CC BY-NC-ND