机器人制孔自适应蚁群路径规划算法

摘要

随着现代飞机制造制孔技术的不断发展,对制孔效率、定位精度及加工质量提出更高的要求.采用CATIA软件建立飞机部件模型,提出自适应蚁群算法并应用于机器人制孔路径规划设计中.仿真实验表明,信息素挥发因子的大小对算法的全局搜索能力及收敛速度有直接影响,提出的自适应蚁群算法通过动态调整信息素挥发因子,充分改善了制孔方式的无目的性、生成的路径质量低等一些不足之处,从而实现机器人制孔路径规划的最优.%With the development of aircraft manufacturing industry robot technology,in the process of modern aircraft manufacturing hole making technology has become more high efficiency,more accurate positioning and more high processing quality,in this paper,the CATIA software is used to build the aircraft component model,adaptive ant colony algorithm is proposed and applied to the design of robot path planning to get the shortest path between the origin and destination point. Simulation experiment result shows that the size of pheromone volatile factor has a direct influence on the global search ability and convergence speed of the algorithm. So adaptive ant colony algorithm adjusts the dynamic of pheromone volatile factor to improve the non-purpose of the way of making holes,the low path quality,and realizes the optimal path planning of robot hole making.