利用光流传感器和速率陀螺仪进行运动估计

Xiaoming Liu, Zhongyuan Chen, W. Chen, X. Xing
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引用次数: 4

摘要

光流传感器(ofs)具有体积小、重量轻、成本低、功耗小、响应快、无辐射等特点,适用于微型飞行器(MAVs)探测周围环境。根据我们最近的工作,除了速度和离地高度外,利用光流传感器和速率陀螺仪还可以获得许多其他的飞行状态,包括攻角、侧滑角、MAV的欧拉角等。本文提出了一种微型飞行器上ofs的布置方案。在建立测量方程的基础上,应用无气味卡尔曼滤波(UKF)对飞行器的飞行状态进行估计。仿真结果表明,该方法可以准确、快速地估计飞行状态。真实值和估计值之间的初始误差将在大约4秒内区分出来。利用这些估计作为反馈,自动驾驶仪可以有效地控制MAV。讨论了ofs的最优布局方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Motion estimation using optical flow sensors and rate gyros
Optical flow sensors (OFSs), with characteristics of small size, light weight, low cost, little power consumption, fast response and no radiation, are suitable for miniature aerial vehicles (MAVs) to detect the environment around them. According to our recent works, besides the velocity and the flight height above the ground, many other flight states can also be obtained using optical flow sensors and rate gyros, including attack angle, sideslip angle, MAV's Euler angles and so on. In this paper, a placement scheme of OFSs on a MAV is proposed. After establishing the measurement equations, an Unscented Kalman Filter (UKF) is applied to estimate the flight states of the MAV. Simulation results show that the flight states can be estimated accurately and quickly. The initial error between the true values and the estimations will be distinguished in about 4 seconds. Using the estimations as feedbacks, the autopilot can control the MAV effectively. Optimal placement scheme of OFSs is also discussed.
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