Keypoints matching is a pivotal component for many image-relevant applications such as image stitching, visual simultaneous localization and mapping (SLAM), and so on. Both handcrafted-based and recently emerged deep learning-based keypoints matching methods merely rely on keypoints and local features, while losing sight of other available sensors such as inertial measurement unit (IMU) in the above applications. In this paper, we demonstrate that the motion estimation from IMU integration can be used to exploit the spatial distribution prior of keypoints between images. To this end, a probabilistic perspective of attention formulation is proposed to integrate the spatial distribution prior into the attentional graph neural network naturally. With the assistance of spatial distribution prior, the effort of the network for modeling the hidden features can be reduced. Furthermore, we present a projection loss for the proposed keypoints matching network, which gives a smooth edge between matching and un-matching keypoints. Image matching experiments on visual SLAM datasets indicate the effectiveness and efficiency of the presented method.

High precision overlay alignment is of great importance to guarantee the quality of Roll-to-Roll printed electronics (R2RPE) products. Aiming at removing machining and assembling errors of the roller with both support and transport uses, an aerostatic bearing device with arrayed restrictors is proposed. In this paper the design of the whole device is presented. The mathematical model of the air film existed between the flexible substrate and the aerostatic bearing device is given by adopting simplified Navier-Stokes equations. In order to modeling the pressure distribution of the air film, numerical simulation is processed with Computational Fluid Dynamics (CFD) software FLUENT. Load capacity curve and stiffness cure are generated to optimize the size and distribution of restrictors on the device. The simulation results indicate that: 1) air film with homogeneous pressure distribution is obtained from the designed arrayed restrictors; 2) diameter of the restrictors has a major influence on load capacity and stiffness when the number of the restrictors reaches a certain quantity.

This paper presents a geometric calibration approach of a permanent magnet (PM) spherical actuator to improve its positioning accuracy. The proposed actuator consists of a ball-shaped rotor with multiple PM poles and a spherical-shell-shaped stator with circumferential air-core coils. Due to manufacturing and assembly restrictions, the actual geometric parameters of the spherical actuator differ from their nominal values. Hence, the identification of such errors is significant for high accuracy motion control. The calibration model is formulated based on the differential form of torque equation. To identify the position vector errors in the magnetization axes of PM poles and coils axes, an iterative least-squares algorithm is employed. The proposed calibration method can also be applied to other PM spherical actuators. To verify the robustness and effectiveness of the proposed calibration algorithm, simulations are conducted on the spherical actuator. The results have shown that the positioning accuracy of the spherical actuator is greatly improved after calibration.

I put forward a new interpolation called Adams-Bashforth interpolation of NURBS (Non-Uniform Rational B-Splines) curve in order to realize higher precision under the condition of satisfying the speed demand. IN this method, I calculated next parameter point by Adams-Bashforth equation and I used difference equation instead of derivation. I simplified and approximated the interpolation algorithm so that the speed and precision of interpolation could be ensured. Finally, we conducted simulations on this interpolation based on MATLAB and compared it with Taylor expansion algorithm so that we could prove its feasibility and correctness. We can conclude that it has a higher precision.

This paper presents a three-DOF permanent spherical actuator, with precise measurement system. As magnetic model is very useful to torque model and control model, magnetic model is the basis of spherical actuator study. A new analytical magnetic field model is presented for the proposed 3-DOF spherical actuator in this paper. This analytical magnetic field method combines the Laplace equation with the equivalent magnetic charge law, which is simple and accurate. Finally, we apply the finite-element magnet analysis method to verify the accuracy of the proposed analytical method.

The study in this paper covers torque modeling, trajectory planning and optimization control of current input of spherical actuators, in which the latter two are the major contributions. Trajectory planning is an effective way to improve the smoothness and stability of rotor motions. A novel three-dimensional (3D) orientation representation method based on manifold of S2is proposed to facilitate the trajectory planning of rotor. Current redundancy of spherical actuator is analyzed in detail, and optimization algorithm of current input is developed to improve the power efficiency and the fault tolerance capability of system. Simulation is then carried out to validate the proposed method and algorithm in this study. The simulation results indicate that by using the trajectory planning, the given torque values and the torque model, optimal current could be obtained to drive the rotor to achieve desired motions.