在往返时间的边际建模中适合的良性,用于网络机器人传感器传输的往返时间
Juan-Antonio Fernández-Madrigal1, Vicente Arévalo-Espejo1, Ana Cruz-Martín1
1Systems Engineering and Automation Department, Institute for the Research in Mechatronic Engineering and Cyberphysical Systems, University of Málaga, 29004 Málaga, Spain.
Sensors (Basel, Switzerland)
|September 13, 2025
概括
本研究涉及模拟远程机器人操作的往返时间. 它提出了分析这些延迟的新统计方法,改进了实时机器人控制.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 网络化系统 网络化系统
- 统计建模 统计建模
背景情况:
- 远程机器人操作需要传输数据和操作,从而导致可变的往返时间.
- 对这些延迟的准确建模对于在严格的时间限制下运行的机器人至关重要.
- 现有的时间序列模型在计算上昂贵,可能不适合实时应用.
研究的目的:
- 开发和评估用于远程操作机器人系统中往返时间边际建模的假设测试.
- 为了应对网络通信制度的突然变化.
- 适应现有的统计模型和适合性测试,以应对网络机器人的特定挑战.
主要方法:
- 对往返时间数据的Log-logistic,Log-normal和指数模型的分析.
- 修改参数估计器和引入适合性测试的新值.
- 使用来自真实和模拟网络机器人场景的数据集进行评估.
主要成果:
- 拟议的修改和新的值提高了边际模型的统计稳定性.
- 这些方法通过广泛的计算分析 (>2100小时) 得到验证.
- 这项研究证明了网络机器人应用的实际适用性.
结论:
- 开发的假设测试和修改的模型是有效的边际建模的往返时间在远程机器人.
- 这些方法为复杂的时间序列预测提供了一个计算效率高的替代方案.
- 这些发现有助于实现更可靠,更响应的远程操作机器人系统.
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