通过分析包装流水线的生产流程，针对复杂的多约束条件下的 Delta 并联机器人分拣动态变化的多目标问题，提出了分节拍的基于改进遗传算法的并联机器人分拣拾取路径优化方法． 经过分析分拣策略，把实际问题转换为类似旅行商问题( TSP) ，并结合其工艺的特殊性提出一种改进遗传算法; 引入分节拍的处理思想，通过将约束条件变成一种染色体裂变和合并操作结合的遗传算子，对每个节拍内的分拣路径进行优化． 试验结果表明，该方法与传统方法相比能够有效缩短分拣行程，平均提高效率 14． 76%．

By analyzing the production process of packaging lines and aiming at the multiple-target problem of the Delta parallel robot sorting with dynamically changing positions under complex multi-constraint conditions,a me- thod to optimize the sorting trajectories of the parallel robot is proposed based on an improved genetic algorithm and the thought of beats.By analyzing the sorting strategy,the practical problem is transformed into a similar traveling salesman problem (TSP),and an improved genetic algorithm is put forward according to the particularity of the sorting process.Moreover,the thought of beats is introduced,and the sorting trajectories in every beat are opti- mized by transforming the constraint conditions into a genetic operator combining the fission and merge operations of chromosomes.The test results show that,as compared with the traditional methods,the proposed method can ef- fectively shorten the average sorting stroke,with an average efficiency increase of 14. 76%.