CAPER: A Connectivity-Aware Path Planner with Regulatory Compliance for UAVs
CAPER: A Connectivity-Aware Path Planner with Regulatory Compliance for UAVs
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CAPER：具有无人机监管合规性的连接感知路径规划器
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Jim Feng
中科院分区：
文献类型：
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作者：
A. Mujumdar;Pooja Kashyap;S. Mohalik;Jim Feng
连接良好、符合法规的飞行路径对于无人机在关键任务应用中的应用至关重要。在本文中，我们提出了连通性感知路径规划与监管合规性（CAPER）：规划安全的解决方案，蜂窝连接的无人机路径的环境与异构连接区域，使规划的路径符合监管禁飞区和高度限制。CAPER建立在基于采样的规划器快速探索随机树（RRT）的基础上，并在规划器和碰撞检测器中进行了一些算法修改。RRT在机器人路径规划中得到了广泛的应用，因为它能够快速搜索高维空间中的可行路径。然而，在现实空间中采用RRT进行连通性感知路径规划问题存在一些挑战，CAPER试图缓解这些挑战。在本文中，我们详细介绍CAPER，并提出其在两个现实的城市环境中实施的结果在斯德哥尔摩和洛杉矶。由于CAPER是建立在随机算法RRT上的，我们还对同一环境中的多次运行进行了简要分析。
Well-connected, regulatory compliant flight paths are crucial for UAVs to be adopted in mission-critical applications. In this paper, we present the Connectivity-Aware Path plannEr with Regulatory compliance (CAPER): a solution for planning safe, cellular-connected UAV paths in environments with heterogeneous connectivity regions, such that the planned paths comply with regulatory no-fly zones and height constraints. CAPER builds on the sampling-based planner Rapidly-exploring Random Trees (RRT), and makes a number of algorithmic modifications both in the planner and the collision detector. RRT has seen widespread use in planning paths in robotics, due to its ability to quickly search high dimensional spaces for feasible paths. However, several challenges exist in adopting RRTs for the connectivity-aware path planning problem in realistic spaces, which CAPER seeks to alleviate. In this paper we detail CAPER, and present results of its implementation in two realistic urban environments in Stockholm and Los Angeles. Since CAPER is built on the randomized algorithm RRT, we also present a brief analysis of multiple runs within the same environment.