An optimized feedrate scheduling method for CNC machining with round-off error compensation

International Journal of Advanced Robotic Systems

et al. 2019

Self Cite

Parametric interpolation for spline plays an increasingly important role in modern manufacturing. It is critical to develop a fast parametric interpolator with high accuracy. To improve the computational efficiency while guaranteeing low and controllable feedrate fluctuation, a novel parametric interpolation method based on prediction and iterative compensation is proposed in this article. First, the feedrate fluctuation and Taylor's expansion are analyzed that there are two main reasons to reduce the calculation accuracy including the truncation errors caused by neglecting the high-order terms and discrepancy errors between the original curve and the actual tool path. Then, to reduce these errors, a novel parametric interpolation method is proposed with two main stages, namely, prediction and iterative compensation. In the first stage, a quintic polynomial prediction algorithm is designed based on the historical interpolation knowledge to estimate the target length used in the second-order Taylor's expansion, which can improve the calculation accuracy and the convergence rate of iterative process. In the second stage, an iterative compensation algorithm based on the secondorder Taylor's expansion and feedrate fluctuation is designed to approach the target point. Therefore, the calculation accuracy is controllable and can satisfy the specified value through several iterations. When finishing the interpolation of current period, the historical knowledge is updated to prepare for the following interpolation. Finally, a series of simulations are conducted to evaluate the good performance in accuracy and efficiency of the proposed method.

Section: Simulation Validationmentioning

confidence: 99%

A parametric interpolation method based on prediction and iterative compensation

Zhang

International Journal of Advanced Robotic Systems

et al. 2019

Self Cite

“…Based on the S-shaped displacement equations (5) to (9) and the prediction equations of picking position (10) to (14), the dynamic prediction equation of the workpiece picking position can be presented as follows:…”

Section: Stepmentioning

confidence: 99%

“…12,13 Ni et al proposed some feed rate scheduling methods to improve motion smoothness and efficiency based on S-shaped ACC/DEC algorithm. 14,15 The linear ACC/DEC algorithm 16 and polynomial algorithm 17 are also utilized to generate smooth feed rate profile. Liu et al 18 used modified trapezoidal ACC/DEC method to plan the sorting trajectory of the Delta parallel manipulator.…”

Section: Introductionmentioning

confidence: 99%

Trajectory planning method of robot sorting system based on S-shaped acceleration/deceleration algorithm

International Journal of Advanced Robotic Systems

Zhang

et al. 2018

Self Cite

To improve the sorting accuracy and efficiency of sorting system with large inertia robot, this article proposes a novel trajectory planning method based on S-shaped acceleration/deceleration algorithm. Firstly, a novel displacement segmentation method based on assumed maximum velocity is proposed to reduce the computational load of velocity planning. The sorting area can be divided into four parts by no more than three steps. Secondly, since the positions of workpieces are dynamically changing, a dynamic prediction method of workpiece picking position has been presented to consider all the possible positions of the robot and the workpiece, so as to realize the picking position prediction of the workpiece at any positions. Each situation in this method can constitute an equation with only one solution, and the existence of the solution can be verified by the proposed graphical method. The simulations of the motion time of the sorting process show that the proposed method can significantly shorten the sorting time and improve the sorting efficiency compared with the previous method. Finally, this method was applied to the Selective Compliance Assembly Robot Arm (SCARA) robot for experiments. In the physical picking experiment, the missing-pick rate was less than 1%, which demonstrates the efficiency and effectiveness of this method.

“…On the other hand, one of the key factors to deliver the smooth feedrate profile is to confine jerk under a specific limit. Thus, many jerk-limited feedrate designs, such as time-optimal [13,14], sine-shape [15], and S-shape [16][17][18], were introduced. Among others, the S-shape feedrate design is commonly adopted due to its simplicity and smoothness.…”

Section: Introductionmentioning

confidence: 99%

“…Among others, the S-shape feedrate design is commonly adopted due to its simplicity and smoothness. Du et al investigated a complete S-shape feedrate scheduling approach (CSFA) [17], while analytical feedrate scheduling methods Time-optimal Feedrate Scheduling with Actuator Constraints for 5-axis Machining Woraphrut Kornmaneesang and Shyh-Leh Chen I with various modified S-shape designs were presented in [18]. Nonetheless, the aforementioned works were dedicated to only bi-or tri-axis translational machining.…”

Section: Introductionmentioning

confidence: 99%

Time-optimal feedrate scheduling with actuator constraints for 5-axis machining

Kornmaneesang

Int J Adv Manuf Technol

2022

Cycle time minimization is one of the major goals that many manufacturers are eager to achieve. Maximizing feedrate is the direct solution, however, physical motions need to be under the specified motion limits to avoid high-frequency vibration, causing machining error. In this paper, a time-optimal feedrate scheduling approach for 5-axis G1 toolpath is presented for 5-axis machining. A quintic B-spline corner smoothing method is utilized to smoothen sharp corners in the toolpath. Then, the S-shape feedrate profile of each block is optimized under the actuator motion constraints, with the objective of minimizing the cycle time. Particle swarm optimization (PSO) is used to provide the optimized solution. Experiments are conducted to validate the proposed approach and the results are compared with two other existing approaches. It is found that the proposed method can achieve shorter cycle time and less contour errors, showing the effectiveness of the proposed approach.