精准农业中的自主无人地面车辆- VELOS项目

Antonios Chatzisavvas, M. Dasygenis, M. Louta
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引用次数: 2

摘要

精准农业的一个方面是使用智能地面或空中交通工具对植物或土壤进行定期自主检查。虽然文献中已经发表了关于智能农用车的文章,但我们发现无论是在硬件还是软件方面,仍然有很多可以改进的地方。在回顾了所有相关工作后,我们确定了需要改进的关键特性,因此我们提出了一种无人驾驶地面车辆(UGV)的构建,可以主动采取行动减少作物的潜在病害。在设计UGV时,重点放在结构的坚固性和耐久性上。所开发的导航算法利用实时数据来规划最优路线,以确保与覆盖距离相关的最优能源效率。为了达到最佳效果,我们使用了位置优化算法。通过这种方式,我们实现了涂层车辆在各种线性作物中的使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Autonomous Unmanned Ground Vehicle in Precision Agriculture – The VELOS project
One of the dimensions of precision agriculture is the use of intelligent ground or air vehicles for periodic autonomous examination of plants or soil. Although there are published articles on smart agricultural vehicles in the literature, we have discovered that there are still many improvements that can be achieved either in hardware or software. After reviewing all the related works, we decided on the key features that need to be improved and thus we present the construction of an Unmanned Ground Vehicle (UGV) that can act proactively to reduce potential diseases in crops. In designing the UGV, emphasis was placed on the robustness and durability of the structure. The developed navigation algorithm takes real-time data to plan the optimal route to ensure optimal energy efficiency in relation to the distance covered. To achieve optimal results, we use position optimization algorithms. In this way we achieve the use of the coated vehicle in various linear crops.
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