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Autonomous Exploration for Infrastructure Modeling with a Micro Aerial Vehicle

机译:微空气车辆基础设施建模的自主探索

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Micro aerial vehicles (MAVs) are an exciting technology for mobile sensing of infrastructure as they can easily position sensors in to hard to reach positions. Although MAVs equipped with 3D sensing are starting to be used in industry, they currently must be remotely controlled by a skilled pilot. In this paper we present an exploration path planning approach for MAVs equipped with 3D range sensors like lidar. The only user input that our approach requires is a 3D bounding box around the structure. Our method incrementally plans a path for a MAV to scan all surfaces of the structure up to a resolution and detects when exploration is finished. We demonstrate our method by modeling a train bridge and show that our method builds 3D models with the efficiency of a skilled pilot.
机译:微空气车辆(MAVS)是一种令人兴奋的基础设施感测的令人兴奋的技术,因为它们可以容易地将传感器放在难以到达位置。虽然配备3D感测的MAV是在工业中使用的,但他们目前必须由熟练的飞行员远程控制。在本文中,我们提出了一种探索路径规划方法,适用于配备Lidar等3D范围传感器的MAV。唯一用户输入的用户输入需要围绕结构的3D边界框。我们的方法逐步计划MAV的路径,以将结构的所有表面扫描到分辨率并检测探索完成后。我们通过建模火车桥来展示我们的方法,并表明我们的方法以熟练的飞行员的效率构建3D模型。

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