Research Articles
Vol. 12 No. sp4 (2025): Recent Advances in Agriculture by Young Minds - III
High-capacity agricultural UAV with DEM-based terrain following and lidar obstacle avoidance for precision spraying application
Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai 600 062, Tamil Nadu, India
Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai 600 062, Tamil Nadu, India
Abstract
This study presents the development and evaluation of a novel high-capacity agricultural unmanned aerial vehicle (UAV) system designed to enhance precision spraying in paddy fields. The UAV features a 30 L payload capacity and integrates Digital Elevation Model (DEM) data for terrain-following flight control, along with an RP LiDAR-based obstacle avoidance system. Field experiments (n=18) conducted across 10.1 hectares in Denkanikotta, Krishnagiri district, Tamil Nadu in 2024 demonstrated that DEM integration with Pixhawk flight controllers achieved a mean height deviation of ±0.18 m from the target spray height, ensuring stable flight operations. The LiDAR system exhibited 96.4 % detection accuracy, effectively identifying and avoiding obstacles within a 15-38 m range, contributing to safer UAV navigation. Spray distribution analysis revealed a coefficient of variation of 9.2 %, significantly lower than conventional UAV spraying methods (16.3 %, p<0.001), indicating improved uniformity and efficiency. Additionally, the system achieved a coverage rate of 3.8 ha/hr, with a 32 % reduction in chemical usage while maintaining equivalent pest control efficacy (92.3 % vs. 90.8 % for conventional spraying, p=0.31). Statistical analysis confirmed a strong correlation (r=0.72, p<0.001) between terrain-following accuracy and spray uniformity, emphasizing the importance of precision altitude control in UAV-based agricultural applications. These findings underscore the potential of high-capacity UAVs with terrain-following capabilities to optimize spray distribution, enhance agricultural efficiency and promote sustainable pest management practices. The integration of DEM data and LiDAR-based obstacle avoidance significantly improves UAV functionality, providing an innovative approach to precision spraying in paddy cultivation.
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