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阐述航天器交会对接最终逼近段相对状态测定与控制算法。测定算法适用于计算机视觉系统,根据标志点构型几何特征,建立非线性测距方程组并构造加权目标函数。对非共面标志点构型(如3点T型与5点锥型)和共面标志点构型(如正方形、矩形、菱形),目标函数均含标志点间距比率关系项;对共面构型,目标函数还包含共面条件项。按最小二乘法,采用Gauaa-Newton数值迭代法求解测距最佳值;对共面标志点四边形构型,利用对角线交点的虚影像坐标确定测距求解迭代初值。获得测距后即可应用四元数估算法确定相对姿态与相对位置。对相对姿态控制算法,给出相对姿态运动学与动力学方程,讨论相平面法与四元数反馈法的控制设计方法。相平面控制法应用常值推力,针对小姿态角机动的特点,将相对姿态通道解耦为三个独立的二阶子系统,设计相平面推力方向切换函数;四元数反馈法应用本征轴旋转的线性二阶系统瞬态响应特性,选择相对四元数与相对角速率反馈增益系数,确定控制力矩。对相对位置控制算法,将实际位移对标称位移之差作为控制变量,阐述所需速度增量最小的双冲量机动。大量模拟计算结果表明相对状态测定与控制算法是有效的。 相似文献
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Abstract Human navigation in an unknown environment requires an understanding of the spatial relationships of the terrain. For example, a soldier who is on a reconnaissance mission in a new city needs to “know” the spatial layout of the surroundings with high confidence. Oftentimes, this understanding must be acquired within a very short amount of time and with limited sensory inputs. The soldier would benefit from a digital avatar that draws inferences about the spatial layout of the city based on an initial set of observations and guides the soldier either in further exploring the environment or in making decisions based on these inferences. In this paper, we present and evaluate an inductive approach to learning spatial associations using sensory data that is available from the simulation environment of a computer game, Unreal Tournament. We study two kinds of spatial relationships between nodes on a level of a game map: nodes that are placed near each other to satisfy some spatial requirement and nodes that are placed near each other to satisfy the design preferences of a level architect. We show that we can infer both kinds of relationships using an association rule mining algorithm. Furthermore, we show how to use an ontology to distinguish between these relationships in order to discover different types of spatial arrangements on a specific map. We discuss how the inferred associations can be used to control an avatar that makes recommendations for navigating unexplored areas on a map. We conclude with some thoughts on the applicability of our methods to scenarios in the real world, beyond the simulation environment of a game, and on how the learned associations can be represented and queried by a simple question-answer type system. 相似文献
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针对插头锥套式自主空中加油过程中加油锥套的识别跟踪问题,提出了一种基于Cam Shift的视觉识别跟踪算法。选取加油锥套跟踪视觉特征,将RGB空间图像转换到HSV色彩空间,并采用自适应阈值算法分割图像。运用最小二乘椭圆拟合算法解算锥套在图像中的中心点坐标;根据目标像素位置变换速度,对Mean Shift算法的目标搜索窗宽进行自适应修正;定义基于巴氏系数的阈值函数,处理锥套被遮挡的情况;将VC与Open CV相结合,设计了加油锥套视觉跟踪软件,对锥套位置进行实时解算和显示。试验结果表明,该算法可达到毫米级精度,满足自主空中加油视觉导航的技术要求。 相似文献
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Wei LIU Xin MA Ling CHEN Zhenyuan JIA Weixiao LIU Xiao LI Jiakun ZHANG Jiwen LU 《中国航空学报》2018,31(1):89-98
The measurement of position and attitude parameters for the isolated target from a high-speed aircraft is a great challenge in the field of wind tunnel simulation technology. This paper proposes a remote-controlled flexible pose measurement system in wind tunnel conditions for the separation of a target from an aircraft. The position and attitude parameters of a moving object are obtained by utilizing a single camera with a focal length and camera orientation that can be changed based on different measurement conditions. Using this proposed system and method, both the flexibility and efficiency of the pose measurement system can be enhanced in wind tunnel conditions to meet the measurement requirements of different objects and experiments, which is also useful for the development of an intelligent position and attitude measurement system. The position and the focal length of the camera also can be controlled remotely during measurements to enlarge both the vertical and horizontal measurement range of this system. Experiments are conducted in the laboratory to measure the position and attitude of moving objects with high flexibility and efficiency, and the measurement precision of the measurement system is also verified through experiments. 相似文献
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对大数据背景下科学研究模式新的变化进行了剖析,探讨了"战略性阅读"的由来及内涵,然后以"战略性阅读"的支持工具之一HistCite为例,以"数字图书馆"主题领域为宏知识来源,研究了如何运用引文分析工具来支持用户对海量数据进行深度分析。 相似文献
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《中国航空学报》2022,35(10):254-264
Skin defect inspection is one of the most significant tasks in the conventional process of aircraft inspection. This paper proposes a vision-based method of pixel-level defect detection, which is based on the Mask Scoring R-CNN. First, an attention mechanism and a feature fusion module are introduced, to improve feature representation. Second, a new classifier head—consisting of four convolutional layers and a fully connected layer—is proposed, to reduce the influence of information around the area of the defect. Third, to evaluate the proposed method, a dataset of aircraft skin defects was constructed, containing 276 images with a resolution of 960 × 720 pixels. Experimental results show that the proposed classifier head improves the detection and segmentation accuracy, for aircraft skin defect inspection, more effectively than the attention mechanism and feature fusion module. Compared with the Mask R-CNN and Mask Scoring R-CNN, the proposed method increased the segmentation precision by approximately 21% and 19.59%, respectively. These results demonstrate that the proposed method performs favorably against the other two methods of pixel-level aircraft skin defect detection. 相似文献
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