In this paper, to solve the problem of quantitative evaluation of the stability of the unmanned aerial vehicle (UAV) while hovering, a binocular vision relative pose measurement system that can be used for remote control is developed and a characteristic target adapted to the system is designed. Moreover, a feature point extraction algorithm based on known feature constraints and a fast feature point matching algorithm based on projection shape invariant constraints are proposed for fast and accurate extraction and reconstruction of feature point sets. The point cloud registration method of SAC-IA + ICP is used to solve the pose and orientation of the characteristic target. It is verified by simulation that the orientation and angle of the target have registration accuracies of 1.1078mm and 0.0463°, respectively. The binocular system is experimentally analyzed using the laser tracker and T-Mac measurement as the true value. Compared with the optical flow method, the former time is shortened by 60%, the Euclidean displacement measurement error is reduced by 83%, and the attitude angle deflection measurement error is reduced by 87%. Then, the hovering state of the UAV is measured using the binocular system; and the obtained experimental measurement results of the system are true and reliable.

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A vision-based mechanical vibration measurement method is presented and verified by experiments in this paper. The coded illumination is projected on the objects by a digital light processing projector with a digital micromirror device in it. The projection patterns are designed to be concentric. In one integration time of the camera, the projector is exposed several times, which embeds temporal information in the images. A single frame can be divided into subframes by separating the coded concentric patterns. The centroids of the coded concentric patterns are fitted, and the centroids are treated as virtual feature points with vibration information. The acquisition devices are common low-speed cameras, and they record the vibration whose frequency exceeds the camera frame rate. The temporal resolution is increased by 10 times, corresponding to the 400 Hz sampling frequency in the experiment. We can measure the vibration of multiple points with different sampling frequencies. The frequency measurement accuracy is in the subhertz level in low-frequency measurement, relative error is always slightly greater than 0.01 in high-frequency measurement, and the amplitude resolution is 130 µm.

Purpose Laser absolute distance measurement has the characteristics of high precision, wide range and non-contact. In laser ranging system, tracking and aiming measurement point is the precondition of automatic measurement. To solve this problem, this paper aims to propose a novel method. Design/methodology/approach For the central point of the hollow angle coupled mirror, this paper proposes a method based on correlation filtering and ellipse fitting. For non-cooperative target points, this paper proposes an extraction method based on correlation filtering and feature matching. Finally, a visual tracking and aiming system was constructed by combining the two-axis turntable, and experiments were carried out. Findings The target tracking algorithm has an accuracy of 91.15% and a speed of 19.5 frames per second. The algorithm can adapt to the change of target scale and short-term occlusion. The mean error and standard deviation of the center point extraction of the hollow Angle coupling mirror are 0.20 and 0.09 mm. The mean error and standard deviation of feature points matching for non-cooperative target were 0.06 mm and 0.16 mm. The visual tracking and aiming system can track a target running at a speed of 0.7 m/s, aiming error mean is 1.74 pixels and standard deviation is 0.67 pixel. Originality/value The results show that this method can achieve fast and high precision target tracking and aiming and has great application value in laser ranging.