Trajectory Optimization of Glue Spraying on Athletic Footwear Sole Based on Multivariable Spray Torch Model

Adopt robot arm for automatic spraying of footwear soles to solve the problems of low efficiency of manual spraying and substandard quality of spraying glue. Established a spray torch model with the pressure of the spraying swath $p_{f}$ , the atomizing pressure $p_{w}$ , spraying flow $q$ , spraying distance $h$ , and spraying angle $\theta $ as the variables, a visual trajectory offset function was established by introducing the sidewall $L$ of the sole and the normal vector $\overline n$ of the trajectory point, and the B-spline curve was used for interpolation to the offset trajectory. The improved non-dominated sorting genetic algorithm (INSGA-Ï) was adopted to solve the spraying trajectory with time, energy, and smoothness as the objectives. A normalized weight function was established that treated the three objectives with equal importance to optimize the solutions. Furthermore, a simulation to optimize the glue spray trajectory and glue spraying experiments were conducted on the sidewall of a shoe sole with a size of 41. As revealed in the results, provided that energy and smoothness are ensured, the proposed model can spray glue on the sidewall of the footwear sole uniformly within 7.27 s, no glue overflow and leakage phenomenon, and the spraying effect is uniform, peeling strength is more than 2.5Kgf/cm, greater than the process requirements of the index, and solved the bottleneck of shoe sole spraying.