In order to solve the problem of the traditional iterative closest point algorithm (ICPA), which requires a high initial position of point cloud and improves the speed and accuracy of point cloud registration, a new registration method is proposed in this paper. Firstly, the rough registration method is optimized. As for the extraction of the feature points, a new method of feature point extraction is adopted, which can better keep the features of the original point cloud. At the same time, the traditional point cloud filtering method is improved, and a voxel idea is introduced to filter the point cloud. The edge length data of the voxels is determined by the density, and the experimentally verified noise removal rates for the 3D cloud data are 95.3%, 98.6%, and 93.5%, respectively. Secondly, a precise registration method that combines the curvature feature and fast point feature histogram (FPFH) is proposed in the precise registration stage, and the algorithm is analyzed experimentally. Finally, the two point cloud data sets Stanford bunny and free-form surface are analyzed and verified, and it is concluded that this method can reduce the error by about 40.16% and 36.27%, respectively, and improve the iteration times by about 42.9% and 37.14%, respectively.
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.
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