基于飞机部件数模的机器人制孔路径规划算法研究

发布时间：2018-01-12 23:18

本文关键词：基于飞机部件数模的机器人制孔路径规划算法研究　出处：《沈阳航空航天大学》2017年硕士论文　论文类型：学位论文

【摘要】：随着现代飞机制造业的发展,对飞机装配技术提出了很高的标准。机器人装配系统是基于数字化的方式进行装配,这其中存在了大量的制孔工作,由此需要一种更为高效、高质量的机器人自动加工方案来取代手工钻铆加工制造工艺。只有提高机器人制孔的准确度,才能更好地完成制孔任务。路径规划技术在机器人的研究领域中是最基本最核心的问题。其基本问题是在空间中,能够很精准的确定从初始点到目标点过程中,选择出一条最优的运动轨迹。近年来机器人制孔路径规划技术已成为在国内外航空制造领域的研究热点,是飞机柔性装配技术的一个重要技术和研究方向。本文以某飞机部件为研究对象,应用CATIA数模软件进行飞机部件产品的建模,过程中提取产品三维数模孔位设计信息(孔位置,工艺信息等)并进行处理,为实现机器人自动制孔提供数据基础。通过分析机器人路径规划的基本原理及路径规划算法,采用粒子群算法和蚁群算法对机器人制孔路径优化问题进行求解,在求解过程中找到一条最优路径,以实现机器人路径规划。在解决机器人的路径规划方面,我们通过对这两种算法的仿真结果进行分析。提出一种自适应蚁群算法应用在路径规划中,并进行仿真与比较验证。结果表明:针对机器人制孔路径规划问题,提出的自适应蚁群算法比传统蚁群算法更精确,更稳定。不管是从最短路径上看,还是从迭代的次数上来看,自适应蚁群算法在该方面问题上收敛速度快、使用的时间少和全程路径长度短,明显优于传统蚁群算法。使传统蚁群算法更容易搜索目标,并提高该算法的收敛速度和搜索全局最优值的能力。
[Abstract]:With the development of modern aircraft manufacturing industry, the aircraft assembly technology has been put forward a high standard. The robot assembly system is based on digital assembly, which has a lot of hole making work. Therefore, a more efficient and high quality robot automatic machining scheme is needed to replace the manual drilling and riveting manufacturing process. Only to improve the accuracy of the robot hole making. Path planning technology is the most basic and core problem in the field of robot research. The basic problem is that in space, it can determine the process from initial point to target point very accurately. In recent years, the robot hole-making path planning technology has become a research hotspot in the field of aviation manufacturing at home and abroad. It is an important technology and research direction of aircraft flexible assembly technology. This paper takes a certain aircraft component as the research object, and uses the CATIA software to model the aircraft component product. In the process of product 3D mathematical model hole position design information (hole location, process information, etc.) and processing. Through analyzing the basic principle of robot path planning and path planning algorithm, particle swarm optimization algorithm and ant colony algorithm are used to solve the robot hole making path optimization problem. In the process of solving, an optimal path is found to realize the robot path planning, and in the aspect of solving the robot path planning. By analyzing the simulation results of these two algorithms, an adaptive ant colony algorithm is proposed for path planning, and the simulation and comparison are carried out. The results show that: for robot drilling path planning problem. The proposed adaptive ant colony algorithm is more accurate and more stable than the traditional ant colony algorithm. In terms of the shortest path and the number of iterations, the adaptive ant colony algorithm converges quickly in this aspect. It is better than the traditional ant colony algorithm to search targets more easily and improve the convergence speed and the ability of searching the global optimum value.
【学位授予单位】：沈阳航空航天大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242

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