Coverage Path Planning Optimization Based on Point Cloud for Structural Inspection

In the last years, Unmanned Aerial Vehicles (UAVs) are being increasingly used in different kinds of inspections due to their maneuverability, flexibility, and efficiency. When deployed in the inspection of large structures, such as dam and slopes, the UAV must cover the largest possible area in the most efficient way. This task is denominated Coverage Path Planning (CPP). Determining the ideal path planning in CPP applications is complex due to dynamic obstacles that cannot be modeled beforehand or when a structural problem is identified, making the UAV to re-plain its trajectory. Therefore, this research proposes the use of bio-inspired metaheuristic techniques for real-time coverage path planning. The methodology dynamically adapts the UAV trajectory when structure failures and obstacles are found. The obtained results showed that the system is efficient, and it has adequate performance for large structures inspections.