Intelligent Obstacle Avoidance Control Algorithm for Agricultural Drones in Complex Farmland Environments

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The new algorithm boosts obstacle avoidance and flight stability in UAVs, indicating effective navigation in farmland settings.

The intelligent algorithm achieves obstacle avoidance with an error of less than 2.1 meters in complex farmland environments.
Using an improved YOLOv5 for target detection boosts model accuracy for small targets and dynamic obstacles significantly.
Reinforcement learning combines with adaptive motion control for efficient obstacle avoidance in UAV operations.
Fuzzy logic control methodology enhances flight stability, supporting effective agricultural applications in variable terrains.

Yuan et al. (2025) studied this question.

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