基于机器人总站的分散式多传感器系统使用UAS轨迹估计的审查
Lucas Dammert1, Tomas Thalmann1, David Monetti2
1Research Units Engineering Geodesy and Photogrammetry, Department Geodesy and Geoinformation, TU Wien, 1040 Vienna, Austria.
Sensors (Basel, Switzerland)
|July 12, 2025
概括
本综述探讨了使用机器人总站 (RTS) 进行无人机系统 (UAS) 的精确轨迹估计. 将RTS与内置传感器相结合,可以实现亚厘米精度,这对于GNSS被拒绝的环境至关重要.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 地理学工程 工程地质学
- 航空航天工程 航空航天工程
背景情况:
- 在全球导航卫星系统 (GNSS) 不可靠的情况下,机器人总站 (RTS) 对于精确的轨道估计至关重要.
- 无人机飞行系统 (UAS) 的轨迹估计通常依赖于GNSS,但为了准确性和可用性,需要使用其他方法.
- 尽管RTS具有高精度定位的潜力,但其在UAS轨迹估计中未得到充分利用.
研究的目的:
- 对使用RTS的去中心化多传感器系统进行UAS轨迹估计的专题文献综述.
- 探索RTS与UAS机载传感器 (IMU,激光扫描) 的集成,以提高姿势估计.
- 为了确定挑战和必要的进步,以实现UAS轨迹估计的次厘米准确度,使用RTS.
主要方法:
- 对RTS测量过程现有研究的专题文献综述.
- 对RTS与UAS机载测量 (IMU,激光扫描) 集成的分析.
- 基于RTS的UAS的评估,包括时间同步,大气折射,镜相互作用和图像评估.
主要成果:
- 现有的研究通常涉及基于RTS的UAS轨迹估计的单个组件,但缺乏整合.
- 为了达到亚厘米和亚0.01的准确性,需要结合UAS轨迹估计和RTS校准技术.
- 目前用于无人机的RTS应用程序在现实的动力场景 (距离和速度) 中是有限的.
结论:
- 为了实现高精度定位,需要采用综合方法,将UAS轨迹估计和RTS校准的现有工作结合起来.
- 未来的研究必须解决集成相机成像的时间同步问题,并通过现场测试验证模拟结果.
- 适应现有的综合轨迹估计方法以最佳地纳入RTS数据对于推进UAS导航至关重要.
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