摘要
Catastrophic natural disasters like earthquakes can cause infrastructure damage.Emer-gency response agencies need to assess damage precisely while repeating this process for infrastructures with different shapes and types.The authors aim for an autonomous Unmanned Aerial Vehicle(UAV)platform equipped with a 3D LiDAR sensor to comprehensively and accurately scan the infrastructure and map it with a predefined resolution r.During the inspection,the UAV needs to decide on the Next Best View(NBV)position to maximize the gathered information while avoiding collision at high speed.The authors propose solving this problem by implementing a hierarchical closed‐loop control system consisting of a global planner and a local planner.The global NBV planner decides the general UAV direction based on a history of measurements from the LiDAR sensor,and the local planner considers the UAV dynamics and enables the UAV to fly at high speed with the latest LiDAR measurements.The proposed system is vali-dated through the Regional Scale Autonomous Swarm Damage Assessment simulator,which is built by the authors.Through extensive testing in three unique and highly constrained infrastructure environments,the autonomous UAV inspection system suc-cessfully explored and mapped the infrastructures,demonstrating its versatility and applicability across various shapes of infrastructure.
