建物点検のための自律UAVによる fault 検出と位置推定
Autonomous UAV for Building Monitoring, Detection and Localisation of Faults
建物周囲を自動飛行するUAVがカメラ画像をニューラルネットで解析してひび割れ等の異常を検出し、その位置へ移動して特定するシステムをROS/AirSim上でシミュレーションした研究。
著者: Suhas Thalanki, T Vijay Prashant, Harshith Kumar M B, Shayak Bhadraray, Aravind S, Srikrishna BR, Sameer Dhole
分類: cs.RO
原文アブストラクト
Collapsing of structural buildings has been sighted commonly and the presence of potential faults has proved to be damaging to the buildings, resulting in accidents. It is essential to continuously monitor any building for faults where human access is restricted. With UAVs (Unmanned Aerial Vehicles) emerging in the field of computer vision, monitoring any building and detecting such faults is seen as a possibility. This paper puts forth a novel approach where an automated UAV traverses around the target building, detects any potential faults in the building, and localizes the faults. With the dimensions of the building provided, a path around the building is generated. The images captured by the onboard camera of the UAV are passed through a neural network system to confirm the presence of faults. Once a fault is detected, the UAV maneuvers itself to the corresponding position where the crack is detected. The simulation is done with ROS(Robot Operating System) using the AirSim environment which initializes ROS Wrappers and provides an integrated interface of ROS and AirSim to work with, The UAV is simulated in the same.