Model-Based Analysis of UAV Accurate Landing in Stochastic Turbulent Environments

Deploying Inspection, Maintenance, and Repair (IMR) robots using unmanned aerial vehicles (UAVs) has emerged as a promising method for wind turbine blade inspection due to lower costs and higher accuracy. However, deploying these robots remains a challenge due to the high-speed, turbulent wind environments around wind farms, making it difficult for UAVs to land on turbine blades accurately. Using a novel discrete stochastic turbulent wind field model, this study evaluates a landing strategy for UAVs to land at higher speeds compared to typical UAV landing speed (≤ 0.5 m/s) in turbulent wind fields to minimise lateral landing errors. Based on 4800 simulations performed at various wind speeds (3.0 - 12.0 m/s) and UAV landing speeds (0.5 - 3.0 m/s), it was observed that this landing strategy provides lower mean landing errors (up to 37.7%) compared to existing UAV landing systems when the wind speed is below 9 m/s, improving landing success rates by up to 30%.