## 1 Introduction  
A laser grader faces the problem of unstable high-speed operation during the actual promotion process in a paddy field. Specifically, when the grader is operating at high speed, the leveling accuracy and overall smoothness of the machine are poor [1]. Starting from the basic structure of paddy-field graders, studying their dynamic models, improving the accuracy of control algorithms, and optimizing the design of mechanical structures are effective ways to solve this problem. The laser grader in a paddy field is a rigid flexible coupling multibody system, and the verification of its dynamic model often requires the measurement of the rigid dynamic parameters of the mechanical system, including the positions of points (to obtain the velocity and acceleration) and the attitude angle of the rigid body (to obtain the angular velocity and angular acceleration) [2]. These parameters often need to be repeatedly measured in different time periods to verify the performance of multibody systems. Non-contact measurement technology for determining trajectory and attitude changes of rigid moving targets has become a focus of research with the rapid advancement of science and technology [3, 4]. Visual technologies for measuring the pose of a target are widely used in obtaining motion parameters and mainly involve monocular, binocular, and multi-ocular measurements, with each technology having its advantages and disadvantages. However, whereas binocular and multi-ocular measurements suffer from a small field of view and difficulties in stereo matching, monocular measurements have a simple structure, large field of view, strong real-time performance, and good accuracy. Monocular systems are thus used widely to measure parameters of rigid-body motion [5; 6; 7; 8]. There are two types of monocular visual measurement of pose according to the features selected, namely measurements of cooperative targets [9; 10; 11] and measurements of non-cooperative targets [12; 13; 14]. Among them, the spatial constraint relationship between target feature points in cooperative target pose measurement is controllable, which to some extent limits the application scope but reduces the difficulty of feature extraction, improves the extraction accuracy, and reduces the complexity of the pose calculation. At present, research on cooperative target measurement methods has focused mainly on cooperative target design, feature extraction, pose calculation methods, and pose calculation errors [15; 16; 17; 18; 19]. However, most of the results are based on calibrated camera parameters and there has been little research on the pose estimation problem of cameras with varying focal lengths. In some practical problems, such as the measurement of multiple rigid-body motion parameters addressed in this article, the internal parameters of the camera need to be frequently adjusted and changed, and there are many factors that affect the calibration accuracy of the internal parameters of a camera. It is difficult to accurately determine the internal parameters in the absence of standard equipment. Therefore, research on uncalibrated camera pose estimation technology is also important. The main methods of solving the pose measurement problem of uncalibrated cameras are the classic two-step method [20], direct linear transform (DLT) method [21], [PERSON]'s calibration method [22], P4P and P5P methods [23], and AFUFPnP method [24] proposed by [PERSON] and others. The two-step method is not suitable for dynamic measurement. P4P and P5P methods face noise sensitivity problems because they use fewer control points to estimate internal and external parameters. [PERSON]'s calibration method requires the installation of a planar chessboard on the measured object to ensure accuracy, which is inconvenient in the case of a moving rigid body. The AFUFPnP method is a pose estimation method based on the EPnP [25] and POSIT [26] algorithms. This method has high pose estimation accuracy and calculation efficiency but low execution efficiency.