arXiv:2512.19245eess.SYcs.RO2025-12

无人机着陆时精准估测与移动平台的相对位置姿态。

Vision-Aided Relative State Estimation for Approach and Landing on a Moving Platform with Inertial Measurements

  • 用视觉+惯性数据构建级联观测器,分步估计相对姿态、位置和速度。
  • 在持续激励条件下,系统几乎全局渐近稳定,局部指数收敛。
  • 适用于动态平台着陆场景,尤其适合无人飞行器自主对接任务。

本文研究无人机在接近并降落于任意三维运动平面平台过程中,对两者间相对位置、姿态及速度的估计问题。该估计依赖于双方搭载的惯性测量单元(IMU)数据,以及机载单目相机提供的视觉信息——包括平台中心的视线方向和其平面法向量。提出一种在SO(3)上的互补滤波级联观测器,先重构相对姿态,再通过线性Riccati观测器估计相对位置与速度。在持续激励条件下,证明了两个观测器的收敛性,且级联结构具有几乎全局渐近稳定性和局部指数稳定性。进一步针对平台仅绕法向轴旋转的情形,提出可利用其测量的线加速度恢复未可观测的旋转角,并给出了局部指数收敛的充分条件。所提观测器通过大量仿真验证有效性。

原文摘要 · Abstract (English)

This paper tackles the problem of estimating the relative position, orientation, and velocity between a UAV and a planar platform undergoing arbitrary 3D motion during approach and landing. The estimation relies on measurements from Inertial Measurement Units (IMUs) mounted on both systems, assuming there is a suitable communication channel to exchange data, together with visual information provided by an onboard monocular camera, from which the bearing (line-of-sight direction) to the platform's center and the normal vector of its planar surface are extracted. We propose a cascade observer with a complementary filter on $\mathbf{SO}(3)$ to reconstruct the relative attitude, followed by a linear Riccati observer for relative position and velocity estimation. Convergence of both observers is established under persistently exciting conditions, and the cascade is shown to be almost globally asymptotically and locally exponentially stable. We further extend the design to the case where the platform's rotation is restricted to its normal axis and show that its measured linear acceleration can be exploited to recover the remaining unobservable rotation angle. A sufficient condition for local exponential convergence in this setting is provided. The proposed observers are validated through extensive simulations.

无人机状态估计视觉惯性导航

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