Sparse Tangential Network (SPARTAN): Motion planning for micro aerial vehicles
Sparse Tangential Network (SPARTAN): Motion planning for micro aerial vehicles
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DOI：
10.1109/icra.2013.6630967
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发表时间：
2013-05
期刊：
影响因子：
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通讯作者：
Hugh Cover;Sanjiban Choudhury;S. Scherer;Sanjiv Singh
中科院分区：
文献类型：
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作者：
Hugh Cover;Sanjiban Choudhury;S. Scherer;Sanjiv Singh
在户外操作的微型飞行器必须能够通过茂密的植被和空旷的田野。现有的方法没有利用这种环境的性质。我们设计了一种算法，可以在自由空间中快速规划，并有效地引导绕过障碍物。在本文中，我们提出了SPARTAN（稀疏切向网络）作为一种方法来创建横跨障碍物周围切向表面的稀疏连接图。我们发现，SPARTAN可以在室外环境中自动驾驶车辆，生成计划的速度比目前最先进的（RRT*）快172倍。因此，SPARTAN可以使用轻型飞行器有限的计算资源，以低延迟可靠地提供安全计划。
Micro aerial vehicles operating outdoors must be able to maneuver through both dense vegetation and across empty fields. Existing approaches do not exploit the nature of such an environment. We have designed an algorithm which plans rapidly through free space and is efficiently guided around obstacles. In this paper we present SPARTAN (Sparse Tangential Network) as an approach to create a sparsely connected graph across a tangential surface around obstacles. We find that SPARTAN can navigate a vehicle autonomously through an outdoor environment producing plans 172 times faster than the state of the art (RRT*). As a result SPARTAN can reliably deliver safe plans, with low latency, using the limited computational resources of a lightweight aerial vehicle.