Optimizing Drone Coverage in Agriculture: an Overview and New Approaches

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This article demonstrates a new approach to optimizing drone trajectories in agriculture, highlighting precision agriculture and obstacle avoidance.

The new hybrid method enhances drone route optimization, significantly reducing traveled distance and mission time.
Simulation results show that the proposed approach improves the efficiency of unmanned aerial vehicles in complex agricultural environments.
The ant colony optimization algorithm integrates global planning with local replanning, tackling obstacles and battery limits.
This method features an adaptive mission recovery that ensures coverage continuity and increases drone autonomy for agricultural tasks.

Sineglazov et al. (2025) studied this question.

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This article demonstrates a new approach to optimizing drone trajectories in agriculture, highlighting precision agriculture and obstacle avoidance.