基于交叉的多变量线性回归模型用于估计无人机阵列中的失序
Marta Gackowska1, Piotr Cofta2, Mścisław Śrutek3
1Faculty of Telecommunications, Computer Science and Electrical Engineering, Bydgoszcz University of Science and Technology, Al. prof. S. Kaliskiego 7, 85-796, Bydgoszcz, Poland. marta.gackowska@pbs.edu.pl.
Scientific reports
|August 7, 2023
概括
这项研究引入了一种新模型,以帮助无人机群管理入侵者回避. 该模型使用多变量线性回归来降低组合飞行期间的能源消耗,改进避免碰撞的策略.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 人工智能的人工智能
- 网络化系统 网络化系统
背景情况:
- 在灾难管理等应用中,静态无人机群体面临着不可预测的入侵.
- 在阵营中避开入侵者会增加能源消耗,并影响运营效率.
- 避免成本与形成功能之间的平衡对于群体弹性至关重要.
研究的目的:
- 开发一个预测模型,以优化无人机群形成参数.
- 根据阵营设置,估计入侵者造成的干扰.
- 帮助选择参数值,以尽量减少在避免碰撞期间的能源消耗.
主要方法:
- 使用多变量线性回归来模型入侵者干扰.
- 采用交叉作为衡量干扰量的指标.
- 生成模拟数据来训练和验证回归模型.
主要成果:
- 开发的模型解释了多达54.4%的交叉 (干扰) 的变化.
- 该模型的预测准确性是基线平均交叉估计器的两倍.
- 为无人机群形成的参数选择提供数据驱动的方法.
结论:
- 这种新型模型在预测和管理无人机群中与入侵者相关的干扰方面提供了显著的改进.
- 优化参数选择可以减少能源消耗和增强群体功能.
- 这项研究有助于更强大,更有效的无人机自主操作.
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