Jinyu Liu

Industrial robots provide a flexible and cost-effective solution for machining large workpieces, but their application is often limited by inherent structural properties. Serial articulated robots, in particular, exhibit relatively low, configuration-dependent stiffness, making them susceptible to vibrations during milling that impair the final surface topography. To address this, this paper presents a predictive model for surface topography that integrates the robot’s posture-dependent dynamics with tool vibration. The proposed method begins by establishing an ideal kinematic model of the cutting edge trajectory. Next, the posture-dependent frequency response function is predicted using an inverse distance-weighted algorithm, and the dynamic parameters of the dominant vibration mode are identified. The resulting tool vibration displacements are then calculated by solving the system’s dynamic model and are integrated into the cutting edge’s swept surface. Milling experiments were conducted to validate the model, demonstrating strong agreement between the predicted and measured surface topography.

With the advantages of large working space, low cost and more flexibility, industrial robots have become an important carrier in intelligent manufacturing. Due to the low rigidity of robotic milling systems, cutting vibrations are inevitable and have a significant impact on surface quality and machining accuracy. To improve the machining performance of the robot, a posture optimization approach based on the dynamic response index is proposed, which combines posture-dependent dynamic characteristics with surface quality for robotic milling. First, modal tests are conducted at sampled points to estimate the posture-dependent dynamic parameters of the robotic milling system. The modal parameters at the unsampled points are further predicted using the inverse distance weighted method. By combining posture-independent modal parameters with calibrating the cutting forces, a dynamic model of a robotic milling system is established and solved with a semi-discretization method. A dynamic response index is then introduced, calculated based on the extraction of the vibration signal peaks. The optimization model is validated through milling experiments, demonstrating that optimizing redundant angles significantly enhances milling stability and quality.

Because of their low cost, large workspace, and high flexibility, industrial robots have recently received significant attention in large-scale part machining. However, due to the stiffness limitations in robot joints and links, industrial robots are prone to vibration during milling processes, which leads to poor surface topography. In robotic milling processes, it remains challenging to simulate the surface topography accurately. This paper presents a mathematical model of surface topography combined with the effects of process parameters and tool vibrations in robotic milling. In this method, the kinematic trajectory of the cutting edge is first calculated by considering the cutter geometry, tool eccentricity, tool orientation, and redundancy angle. After that, the posture-dependent dynamic characteristics of the robotic milling system are predicted using an inverse distance-weighted approach. Then, a dynamic model of the robotic milling system is constructed for calculating tool vibration displacements. Finally, the kinematic model of cutting edges is modified using Z-map to incorporate the obtained vibration displacements into the sweep surfaces. In addition, milling experiments are carried out to verify the effectiveness of the proposed method, showing a good agreement between predicted and measured surface roughness. Furthermore, the findings offer valuable insights into the impact of process parameters and robot posture on surface quality.

NURBS curve parameter interpolation is extensively employed in precision trajectory tasks for industrial robots due to its smoother performance compared to traditional linear or circular interpolation methods. The trajectory planning systems for industrial robots necessitate four essential functional modules: first, the spline curve discretization technique ensuring chord error compliance; second, the contour scanning technique for determining the maximum feasible feed rate for multi-constraint and multi-segment paths; third, the technique for achieving a smooth feed rate profile; and fourth, the continuous curve parameter interpolation technique. Therefore, this paper proposes a high-precision planar NURBS interpolation system for industrial robots. Firstly, a segmentation method for NURBS curves based on a closed-loop chord error constraint is proposed, which segments the original global NURBS curve into a collection of Bezier curves that strictly meet the chord error constraint. Secondly, a bidirectional scanning technique is presented to meet the joint space constraint, establishing an analytical mapping between the tool tip kinematic constraint and the joint kinematic constraint. Then, based on the traditional S-shaped feed rate profile, an adaptive algorithm with a displacement constraint is introduced, considering the real-time speed adjustment requirements of robots. Finally, a compensation interpolation strategy based on arc length parameterization is adopted to solve the accumulated error problem in parameter interpolation. The effectiveness of and potential for enhancing the quality of planar machining of the proposed planar NURBS interpolation system for industrial robots are validated through simulations and experiments. The results demonstrate the system’s applicability and accuracy, and its ability to improve planar machining quality.

Geometric deviations and clamping constraints are the two major variation factors in thin-walled structure assembly processes. Geometric deviations are caused by inevitable uncertainties in manufacturing processes and have a significant impact on dimensional control for compliant assembly processes. Due to the flexibility of thin-walled structures, the clamping constraints during assembly greatly affect the compliant deformation of assembled structures. In this paper, a new method based on isogeometric analysis (IGA) considering geometric deviations and clamping constraints is proposed. The geometric deviations of thin-walled structures can be obtained by offsetting along the control points in an ideal part based on Nonuniform Rational B-Splines (NURBS), and the clamping constraints, such as fixture positioning deviations and connection matching deviations, are converted into displacement boundary conditions by the Lagrange multiplier method. Furthermore, the elastic force induced by initial geometric deviations is calculated using Kirchhoff-Love shell elements. Considering the coordination constraint relationship between shape closure and force closure in the compliant assembly process, a variation propagation model is developed using NURBS-based IGA. It integrates geometric deviations and compliant deformations into a unified mathematical representation framework by embedding exact geometry into assembly analysis. In addition, a numerical example is presented to demonstrate the accuracy and effectiveness of the developed method.