Improvement of Clothing Structure Design and Wearing Comfort Based on Jacobi Matrix Optimization Algorithm

Abstract

Clothing structure design is a key link in the clothing manufacturing process, and the traditional design methods rely on the experience and skills of designers. With the development and application of digital technology in the apparel industry, it has greatly promoted the innovation and development of apparel manufacturing. In this paper, we combine the depth estimation and vision controller methods to construct an image Jacobi matrix to realize the control of the hand-eye mapping relationship of the robot's visual servo, which represents the mapping relationship between the robot's joint speed to the end speed. Using Kalman filtering algorithm, the image Jacobi matrix to be estimated is used as the system state to estimate the system state, so as to achieve the control of the stitch and displacement of the garment sewing, and, at the same time, capture the visual information contained in the garment to optimize the design of the garment structure. For the optimized designed garments using the Jacobi matrix, 4# has the highest mean comfort rating of 4.5 and above. The mean value of satisfaction evaluation for ease of movement and overall comfort of the optimized garment went up to 4. It is evident that the overall comfort of the garment optimized by the image Jacobi matrix algorithm has been significantly improved.