Customized hexacopter drone improves UAV stability and data acquisition in coastal environments, suggesting enhanced monitoring capabilities.
In recent years, aerial drones, or unmanned aerial vehicles (UAVs), have significantly expanded across industries such as environmental monitoring, search and rescue, video surveillance, precision agriculture, and coastal applications. The National Institute of Ocean Technology (NIOT), Ministry of Earth Sciences, has developed and customized a 22 kg heavy lift hexacopter drone specifically for marine and atmospheric applications. This UAV is designed for seawater sampling, oceanographic data collection, and coastal topography mapping, equipped with conductivity, temperature, and depth (CTD) sensors, multi-parameter sensors, an automatic seawater sampler, and light detection and ranging (LiDAR) technology. The drone is designed using a reliable Cube Orange flight controller, dual inertial measurement units (IMUs), dual global positioning system (GPS) modules, a dual radio frequency (RF) communication system, and 6 X8 Hobbywing rotors, supporting up to 10 kg of payload with a flight endurance of 30 min. Computational fluid dynamics (CFD) simulations were carried out using SolidWorks® 2024 flow simulation to analyze aerodynamic performance. Transient propeller-induced flow (PIF) studies were performed under varying headwind and crosswind velocities (0–10 m/s). The results show that yaw and roll deviations reached up to 12° and 35°, respectively, under crosswind gusts, and power consumption increased by 23 % in 8 m/s wind conditions, highlighting the effects of coastal wind dynamics on flight stability. These findings are validated using actuator disk theory and further verified by field tests. This study provides valuable insights into the aerodynamic behavior, stability, and energy demands of UAVs in dynamic marine environments, supporting the development of reliable drone-based platforms for sustainable coastal monitoring, oceanographic surveying, and environmental data acquisition.
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Srinivasan et al. (2025) studied this question.
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