This article presents an omnidirectional mobile platform with six mecanum wheels, which provide better carrying capacity than traditional four-wheel platform. Omnidirectional mobile platform with six mecanum wheels can withstand heavier load than the omnidirectional mobile platform with four mecanum wheels, which was used to transport large equipments used in marine and aerospace. Due to the small size, omnidirectional mobile platform with six mecanum wheels move more flexibly and reach desired position and pose easier in narrow workspace, compared with omnidirectional mobile platform with eight mecanum wheels whose disadvantage of large size offsets the advantage of zero turning radius. The kinematic model of the omnidirectional mobile platform with six mecanum wheel is established and verified through four kinds of motion state by the simulation (the omnidirectional mobile platform with six mecanum wheels moving along the Z axis, the X axis, the direction of which angle between positive X is 45°, and the omnidirectional mobile platform with six mecanum wheels rotating around the geometric center). The states of one wheel in failure have been analyzed in this article, taking into account the research levels of omnidirectional mobile platform with six mecanum wheels in the presence. The motion features of the platform with six mecanum wheels and four mecanum wheels are analyzed when certain wheels are locked-up or followed-up based on the force analysis of the wheels, and it proves that the platform with six mecanum wheels moves more stable than the platform with four mecanum wheels. In the presence of wheel failure, the platform still can move to the target location with gesture, due to its redundancy. This study contributes to the research of omnidirectional mobile platform with normal or failure mecanum wheels.

In a robot grinding system, the change of the robot's pose affects the overall stiffness of the whole machining system, which indirectly leads to the irregularity of the grinding surface. For this purpose, we propose a method to enhance the stiffness of the robot. The robot grinding system layout is usually based on the experience of the designer without any quantitative selection criteria. With the introduction of the stiffness performance evaluation index, we decouple the stiffness-couple relationship between the robot pose and layout of the robot system and calculate the value of the stiffness index for evaluating the performance of each layout point as a quantization selection basis. Using Rayleigh quotient as the stiffness performance evaluation index for the manipulator, we obtain a relationship between the stiffness performance and the installation position of the grinding tool. Based on the chosen layout point, we proposed the length of the semi axis along the direction of the grinding force in the stiffness ellipsoid as the optimization objective and obtain the optimal configuration in the entire processing workspace through a genetic algorithm method. Theoretical and numerical simulation is presented to demonstrate the effectiveness of the proposed approach. The results demonstrate that the optimization improves the stiffness performance significantly.

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In the multifocus microscopic image measurement method, the distortion of the three-dimensional (3D) reconstruction model has always been an important factor affecting the measurement result. In spatial domains, the focus measure algorithm is based on the gradient change of the pixel point to determine the degree of focus of the pixel. So it will be difficult to accurately extract the focus of the pixel in the areas where color difference is not obvious, resulting in 3D model distortion. According to the optical principle, the high-frequency coefficients of the clear image are larger than the high-frequency coefficients of the blurred image. Based on this characteristic, this paper proposes a new multifocus microscopic image 3D reconstruction algorithm using a nonsubsampled wavelet transform (NSWT). The NSWT does not consider the downsampling in wavelet decomposition and has translational invariance. Therefore, the wavelet transform value of each pixel can be calculated in the image, so the high-frequency coefficient of each pixel can be obtained; then the convolution calculation is performed on the high-frequency coefficients of the pixel points in the fixed window as the focus measure value of the pixel point. Compared with the traditional algorithm, the algorithm proposed in this paper can show better unimodal and antinoise performance on the focusing measure curve. In this paper, the reconstruction of the experimental object is Alicona standard block triangular and semicylindrical. The proposed algorithm and the traditional algorithm for comprehensive measure use the root mean square error, peak signal to noise ratio, and correlation coefficient as the measure index. The experimental results and comparative analysis prove the correctness of the proposed algorithm and enable more accurate reconstruction of 3D models based on multifocus microscopic images.

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