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Grid-Based Coverage Path Planning With Minimum Energy Over Irregular-Shaped Areas With Uavs

机译:无人机在不规则形状区域上以最小能量进行基于网格的覆盖路径规划

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Grid-based methods have been proposed to solve the Coverage Path Planning problem using Unmanned Aerial Vehicles in irregular-shaped areas since simple geometric flight patterns, such as the back-and-forth, are inefficient in this type of scenario. However, the grid-based methods usually apply simplistic cost functions and demand high computational time leading to inefficient and expensive paths, making them not usable in real-world scenarios. This paper introduces an energy-aware grid-based approach aimed at minimizing energy consumption during mapping missions over irregular-shaped areas. Our work was built upon a previously proposed grid-based approach. Here we introduce an energy-aware cost function based on an accurate energy model. The proposed approach was able to save up to 17% of energy in real flight experiments, proving that the original cost function was not capable of finding the optimal solution in terms of real energy measurements. Additional simulation experiments were also performed to state the energy savings in different irregular-shaped scenarios. As a further contribution, we also applied two pruning techniques to the original approach dropping the computation time up to 99%.
机译:已经提出了基于网格的方法来解决在不规则形状区域中使用无人飞行器的覆盖路径规划问题,因为简单的几何飞行模式(例如来回)在这种情况下效率低下。但是,基于网格的方法通常应用简单的成本函数,并需要大量的计算时间,从而导致效率低下和昂贵的路径,从而使它们无法在实际场景中使用。本文介绍了一种基于能量感知的网格方法,旨在最大程度地减少在不规则形状区域上进行地图绘制时的能源消耗。我们的工作建立在先前提出的基于网格的方法的基础上。在这里,我们介绍一个基于精确能源模型的能源感知成本函数。所提出的方法能够在实际飞行实验中节省多达17%的能量,证明原始成本函数无法在实际能量测量方面找到最佳解决方案。还进行了附加的仿真实验,以说明在不同形状的不规则情况下的节能效果。作为进一步的贡献,我们还对原始方法应用了两种修剪技术,从而将计算时间缩短到99%。

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