Abstract: Aiming at the problem that the quantitative evaluation index of complex surface spraying trajectory was not perfect,a comprehensive optimization method of complex surface spraying trajectory based on multi-factor model and multi-scale genetic algorithm was proposed.Combined with the spraying quality and the motion performance of the robot,the influencing factors of the robot spraying trajectory were analyzed comprehensively,and the multi-factor model of the spraying trajectory was constructed.Then the weight of model factors was determined by using analytic hierarchy process,and the spraying trajectory was evaluated quantitatively.The multi-scale and dynamic evolution strategy was used to improve the genetic algorithm,and the multi-scale genetic algorithm was defined.The multi-scale genetic algorithm was applied to the spraying trajectory optimization of complex surface.The case indicated that the comprehensive evaluation index of spraying trajectory was significantly improved,which could effectively solve the problem of off-line planning of spraying trajectory for complex surfaces.

Key words: complex surface, robot, spraying, genetic algorithms, trajectory optimization

摘要： 针对复杂曲面喷涂轨迹的量化评价指标不够完善,提出基于多因素模型和多尺度遗传算法的复杂曲面喷涂轨迹综合优化方法。首先,结合喷涂质量和机器人运动性能要求,综合分析机器人喷涂轨迹影响因素,构建喷涂轨迹多因素模型。其次,利用层次分析法,确定模型因素权重。然后,采用多尺度、动态进化策略改进遗传算法,定义多尺度遗传算法。最后,将多尺度遗传算法应用于复杂曲面喷涂轨迹综合优化。实例研究表明,喷涂轨迹的综合评价指标得到显著提升,能有效解决复杂曲面喷涂轨迹离线规划难题。

关键词: 复杂曲面, 机器人, 喷涂, 遗传算法, 轨迹优化