To address the problem of low overall machining efficiency of free-form surfaces and difficulty in ensuring machining quality, this paper proposes a MATLAB-based free-form surface division method. The surface division is divided into two stages: Partition area identification and area boundary determination. In the first stage, the free-form surface is roughly divided into convex, concave, and saddle regions according to the curvature of the surface, and then the regions are subdivided based on the fuzzy c-means clustering algorithm. In the second stage, according to the clustering results, the Voronoi diagram algorithm is used to finally determine the boundary of the surface patch. We used NURBS to describe free-form surfaces and edit a set of MATLAB programs to realize the division of surfaces. The proposed method can easily and quickly divide the surface area, and the simulation results show that the proposed method can shorten machining time by 36% compared with the traditional machining method. It is proved that the method is practical and can effectively improve the machining efficiency and quality of complex surfaces.

According to the requirements of the reconnaissance robot for the ability to adapt to a complex environment and the in-depth study of the obstacle climbing mechanisms, a planetary wheel-leg-combined mechanism capable of adapting to complex terrains is proposed. According to the proposed planetary wheel-leg-combined mechanism, the land part of the air-ground amphibious reconnaissance robot is designed. Considering the obstacle and fast marching performance, four groups of combined wheel-leg mechanisms are adopted in the land bank. Under the action of three kinds of obstacles, the stability and the movement ability of the robot are analyzed by using the static method. The parameter model of the reconnaissance robot is built by a virtual prototype dynamics software MSC.ADMAS. The kinematic characteristic curves of each component and the whole prototype are obtained, which provides a theoretical basis for the design and numerical calculation of the robot structure. Finally, the climbing ability tests of the reconnaissance robot prototype verify the reliability and practicability of the body structure of the reconnaissance robot.

To overcome the problem of the high initial position of the point cloud required by the traditional Iterative Closest Point (ICP) algorithm, in this paper, we propose a point cloud registration method based on normal vector and directional histogram features (SHOT). Firstly, a hybrid filtering method based on the voxel idea is proposed and verified using the measured point cloud data, and the noise removal rates of 97.5%, 97.8%, and 93.8% are obtained. Secondly, in terms of feature point extraction, the original algorithm is optimized, and the optimized algorithm can better extract the missing part of the point cloud. Finally, a fine alignment method based on normal vector and directional histogram features (SHOT) is proposed, and the improved algorithm is compared with the existing algorithm. Taking the Stanford University point cloud data and the self-measured point cloud data as examples, the plotted iteration-error plots can be concluded that the improved method can reduce the number of iterations by 40.23% and 37.62%, respectively.

Optical free-form surfaces are often used to manufacture optical components such as lenses and mirrors, and free zone surface optical components are widely used in aerospace optics. To address the issues of low processing quality and overall efficiency in the machining of aluminum alloy free-form surfaces, an efficient numerical control machining method based on surface segmentation has been proposed. The segmentation of free-form surfaces is divided into two stages: the recognition of surface partitions and the determination of surface boundaries. Initially, the free-form surface is roughly classified into three types of regions: convex (planar), concave, and saddle-shaped, based on its curvature characteristics. The surface is then further segmented using the fuzzy c-means clustering algorithm. Subsequently, the Voronoi diagram algorithm is employed to construct the boundaries of the free-form surface ultimately. In a UG simulation, the segmentation machining method was compared with the conventional overall machining method, demonstrating a reduction in the machining path by 12.18% and machining time by 13.92%. Finally, experiments revealed a 12.28% reduction in machining path length and a 12.56% reduction in machining time using the segmentation machining method. This verifies the practicality of the free-form surface segmentation approach and proves that it can effectively enhance machining efficiency and quality.

For 3D point cloud date and model CAD data, this paper proposes an improved point cloud registration algorithm, which is divided into two parts: coarse registration and fine registration. In the coarse registration stage, the voxel algorithm is used to select feature points, and then feature histogram of the points is used to select matching point pairs. The edge feature point algorithm and RANSAC algorithm are combined to eliminate mismatched point pairs. Finally, the quaternion method is used to solve the parameters of the initial registration. In the precise registration stage, the improved coherent point shift (CPD) algorithm is used for precise registration. Experimental results show that the registration accuracy and convergence speed of this algorithm are improved.