Path sorting optimization of painting robots usingestimation of distribution algorithms
基于分布估计算法的喷涂机器人路径组合优化

Considered the characteristics of the path sorting and integration problem in off-line trajectory planning system of spray painting robots, it modeled the integration problem as an open generalized traveling salesman problemGTSP, and established the corresponding cost matrix and optimization objective. In order to solve the problem, this paper proposed an optimization algorithm based on distributed estimation. The algorithm introduced statistical learning into genetic algorithm, and used learning based on the probability model and sampling algorithm to replace the crossover and mutation in genetic algorithm to achieve the evolution of population. So it can get the global optimum effectively. Results of simulations verify the effectiveness and feasibility of this method.