无人直升机视觉着陆中的运动状态估计算法  

Vision-based Movement State Estimation Algorithm for Unmanned Helicopter Landing

作　　者：蒋鸿翔[1] 徐锦法[1] 高正[1] 

机构地区：[1]南京航空航天大学直升机旋翼动力学重点实验室,江苏南京210016

出　　处：《航空学报》2010年第4期744-753,共10页Acta Aeronautica et Astronautica Sinica

基　　金：国防科技重点实验室基金

摘　　要：对无人直升机(UH)视觉着陆中基于视觉图像处理的运动状态估计问题进行了研究。介绍了视觉着陆原理,分析了运动估计、特征图像处理与着陆控制间的关系,推导并建立了UH相对着陆平台位姿估计算法、线速度与角速度估计算法。相邻两帧图像对应特征点像点位置为位姿估计算法提供数据,一帧图像特征点像点位置及其对应像点平移速度为线速度与角速度估计算法提供数据。利用UH着陆控制仿真数据模拟UH着陆运动过程中像点位置及其对应平移速度的视觉图像处理结果。仿真验证了运动状态估计算法,结果表明所提出的运动状态估计算法能有效地利用视觉图像处理结果数据估计出UH的位置、姿态、线速度和角速度。This article studied the movement state estimation based on the vision image process for unmanned helicopter （UH） landing. The vision-based landing principle and scheme is introduced,and the relationship between movement state estimation,feature image process and landing control is analyzed. The movement state estimation algorithms are deduced and modeled,which include a relative position to the landing pad and attitude estimation algorithm,and a velocity and angular rate estimation algorithm. The pixel positions of the corresponding feature points from two sequent image frames are provided for the relative position and attitude estimation algorithm. The pixel positions and pixel translation velocities of the corresponding feature points from one image frame are provided for velocity and angular rate estimation. Simulated imaging data from UH landing control simulation imitated the feature pixel positions and their corresponding pixel translation velocities. Simulation and verification for the movement state estimation is conducted. Simulation results indicate that the proposed movement state estimation algorithm can estimate effectively the position,attitude,velocity and angular rate with the vision image process data.

关 键 词：无人直升机着陆 计算机视觉模型 运动估计 视觉算法仿真 飞行成像数据模拟 

分 类 号：V249.1[航空宇航科学与技术—飞行器设计] TP391[自动化与计算机技术—计算机应用技术]