Fuli Qi and Ling Yang
Drones, intelligent obstacle avoidance, fuzzy control, multi-sensor information fusion, PID
To improve the intelligent obstacle avoidance effect of unmanned aerial vehicles (UAVs), the paper constructs the intelligent obstacle avoidance model of UAVs and proposes the multi-sensor information fusion obstacle avoidance (FOA) method based on fuzzy control. In the experimental results, the proposed method showed higher obstacle avoidance accuracy in terrain threats, other drone threats, and climate threats, with an average accuracy of 97.44%, 94.55%, and 94.28%, respectively. Experimental results showed that the proposed model not only effectively fused information from different sensors but also achieved efficient and stable obstacle avoidance in complex environments. The research aims to improve the obstacle avoidance effect of drones and provide safer guarantees for the use of industrial and civilian drones.
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