用重尾不确定性模型进行概率鸟类轨迹预测,用于低海拔空域监测
Feiyang Song1, Zhonghe Liu2,3, Yuyang Zhao2,3
1Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL 60208, USA.
Sensors (Basel, Switzerland)
|February 27, 2026
概括
本研究介绍了Mini-BirdFormer,这是一个统一的框架,用于预测低海拔空域中的鸟类和无人机飞行路径. 该模型准确地预测轨迹,并检测有校准不确定性的无人机,从而实现安全的共享空域监控.
科学领域:
- 计算机视觉 计算机视觉
- 机器人技术 机器人技术 机器人技术
- 航空航天工程 航空航天工程
背景情况:
- 低空空域越来越多地由鸟类和无人驾驶飞行器 (UAV) 分享,造成了安全问题.
- 现有的轨迹预测方法往往无法解释重尾飞行动态,并且缺乏不确定性校准.
- 目前基于视觉的系统将检测和预测视为单独的任务,限制了现实世界的部署.
研究的目的:
- 开发一个统一的低空空域监测框架,整合轨道预测和无人机检测.
- 通过模拟重尾飞行动态和提供校准的不确定性来解决现有方法的局限性.
- 为共享空域安全提供高效,可部署的解决方案.
主要方法:
- 提出了Mini-BirdFormer,一个轻量级的变压器编码器与一个Student-t混合密度头相结合.
- 模拟重尾飞行动力学,用于准确的鸟类和无人机轨迹预测.
- 集成了一个系统级扩展,用于使用开放词汇学习进行零射击无人机检测.
主要成果:
- 在仅有105万个参数的情况下,实现了强大的长视野轨迹预测性能 (minADE为0.785m).
- 与高斯的LSTM基线相比,显著改善了不确定性校准,将负日志概率从1.25降低到-2.01.
- 在资源有限的平台上在616FPS启用了低延迟推断,并实现了92%的回忆,用于零射击无人机检测.
结论:
- 拟议的框架为监测共享低空空域提供了一个实用和可部署的解决方案.
- 将沉重的概率建模与紧的骨干相结合,可以提高轨迹预测和不确定性估计.
- 该系统有效地解决了无人机在鸟类居住的空域越来越多的存在所带来的安全风险.
相关概念视频
01:29Application of Linearization and Approximation
121
A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...
121
00:59Uncertainty: Overview
1.8K
In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
1.8K
01:26Orthogonal Trajectories
86
Orthogonal trajectories describe the geometric relationship between two families of curves that intersect each other at right angles. One illustrative case involves a family of parabolas that open sideways along the x-axis. These curves share a common shape but differ by a scaling parameter, resulting in a set of curves that all pass through the origin and widen at different rates.Determining Orthogonal TrajectoriesTo identify the orthogonal trajectories for these parabolas, the first step...
86
00:54Uncertainty: Confidence Intervals
11.9K
The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
11.9K
00:59Propagation of Uncertainty from Random Error
2.0K
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
2.0K
01:10Propagation of Uncertainty from Systematic Error
1.5K
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
1.5K