Online inspection path planning for autonomous 3D modeling using a micro-aerial vehicle
Online inspection path planning for autonomous 3D modeling using a micro-aerial vehicle
复制标题
使用微型飞行器进行自主 3D 建模的在线检查路径规划
DOI：
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复制
发表时间：
2017
期刊：
影响因子：
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通讯作者：
Sungho Jo
中科院分区：
文献类型：
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作者：
Soohwan Song;Sungho Jo
在本文中，我们提出了一种利用微型飞行器（MAV）规划探索路径以生成未知环境三维模型的新算法。我们的算法首先确定下一个最佳视图（NBV），使信息增益最大化，并规划一条到达NBV的无碰撞路径。沿着路径，MAV探索最大的未知区域，尽管它有时会错过较小的未重建区域，如洞或稀疏的表面。为了覆盖这样的区域，我们提出了一种在线检测算法，该算法始终如一地实时提供通往NBV的最佳覆盖路径。该算法根据获取的信息迭代地细化检测路径，直到完成特定局部区域的建模。我们通过模拟实验将所提出的算法与其他最先进的方法进行比较，从而评估了所提出的算法。结果表明，我们的算法在探索和3D建模场景中都优于其他方法。
In this paper, we propose a novel algorithm for planning exploration paths to generate 3D models of unknown environments by using a micro-aerial vehicle (MAV). Our algorithm initially determines a next-best-view (NBV) that maximizes information gain and plans a collision-free path to reach the NBV. Along the path, the MAV explores the greatest unknown area although it sometimes misses minor unreconstructed region, such as a hole or a sparse surface. To cover such a region, we propose an online inspection algorithm that consistently provides an optimal coverage path toward the NBV in real time. The algorithm iteratively refines an inspection path according to the acquired information until the modeling of a specific local area is complete. We evaluated the proposed algorithm by comparing it with other state-of-the-art approaches through simulated experiments. The results show that our algorithm outperforms the other approaches in both exploration and 3D modeling scenarios.
影响因子：
3.5
作者：
Hornung, Armin;Wurm, Kai M.;Burgard, Wolfram
通讯作者：
Burgard, Wolfram