Assessing Wind Impact on Semi-Autonomous Drone Landings for In-Contact Power Line Inspection

TL;DR

This paper presents a semi-autonomous drone landing system for power line inspection that evaluates success probabilities under different wind conditions, providing insights into optimal control strategies and wind tolerance.

Contribution

It introduces a novel semi-autonomous landing control scheme for drones on power lines and assesses its robustness under various wind conditions using Monte Carlo simulations.

Findings

Two-stage landing strategies improve success rates.

Optimal controller parameters depend on wind intensity.

System successfully demonstrated in autonomous power line landing.

Abstract

In recent years, the use of inspection drones has become increasingly popular for high-voltage electric cable inspections due to their efficiency, cost-effectiveness, and ability to access hard-to-reach areas. However, safely landing drones on power lines, especially under windy conditions, remains a significant challenge. This study introduces a semi-autonomous control scheme for landing on an electrical line with the NADILE drone (an experimental drone based on original LineDrone key features for inspection of power lines) and assesses the operating envelope under various wind conditions. A Monte Carlo method is employed to analyze the success probability of landing given initial drone states. The performance of the system is evaluated for two landing strategies, variously controllers parameters and four level of wind intensities. The results show that a two-stage landing strategies offers higher probabilities of landing success and give insight regarding the best controller parameters and the maximum wind level for which the system is robust. Lastly, an experimental demonstration of the system landing autonomously on a power line is presented.