基于效率的冲床自动上下料运动和控制策略研究

发布时间：2018-01-18 15:21

本文关键词：基于效率的冲床自动上下料运动和控制策略研究　出处：《安徽工程大学》2017年硕士论文　论文类型：学位论文

【摘要】：尽管机器人自动上下料在企业中已经得到较为广泛应用,技术相对成熟,但电机定转子硅钢片冲压作业要求速度快,效率高,上下料运动轨迹对效率和作业精度影响非常显著。本文针对机械手坐标系建立、轨迹规划方法选择使用遗传算法求解问题等展开技术研究。本文在芜湖安普机器人产业技术研究有限公司"电机定转子片自动化产业升级"项目资助下选取机器人的轨迹规划作为内容研究。具体工作如下:(1)为了深入开展运动轨迹规划研究,本文针对上下料运动特征确定机械手自由度,通过对比机械手关节结构,确定机械手的关节类型。建立了机械手D-H参数模型,分析研究其正逆运动学,并选取特殊点验证了结果的正确性;(2)其次,研究了目前广泛应用的轨迹规划方法:关节插值轨迹规划;笛卡尔空间轨迹规划;笛卡尔空间轨迹规划。通过分析得出了第一种轨迹规划关节差值曲线有局限性,无法保证整条轨迹曲线光滑;第二种轨迹规划计算量比较大,而且由于轨迹规划非常直观,难以保证有奇异点;相对而言,第三种轨迹规划可以保证整条轨迹的连续性,计算量较小;(3)通过上述的对比研究,选取B样条曲线为轨迹规划拟合曲线。以时间最短为目标,通过遗传算法全局寻优搜索一条时间最短的轨迹,采用MATLAB对遗传算法进行仿真;(4)最后,选用现有埃夫特ER20-C10工业机器人进行模拟实验,记录了机器人各个关节运动时间与关节轨迹图等各种参数。取得主要成果如下:(1)建立了机械手的空间位姿表示方法,并求出其正逆解。对比研究了几种轨迹规划方法;(2)通过MATILAB仿真优化了机器人各段工位的时间,整个关节曲线趋于平滑,验证了优化方法的可行性;(3)实验结果表明,轨迹规划结果明显减少了工业机器人上下料时间,最多减少了 7.3809s。
[Abstract]:Although the robot automatic loading and unloading has been widely used in enterprises, the technology is relatively mature, but the speed and efficiency of motor stator and rotor silicon steel sheet stamping is high. The movement trajectory of loading and unloading has a significant effect on efficiency and precision. This paper establishes the coordinate system for manipulator. Trajectory planning method selection using genetic algorithm to solve problems and other technical research. This paper in Wuhu Anpu Robot Industry Technology Research Co., Ltd. "Motor stator and rotor blade automation industry upgrade" The trajectory planning of the robot is selected as the content of the project. The specific work is as follows: (. 1) in order to carry out the research of motion trajectory planning deeply. In this paper, the degree of freedom of manipulator is determined according to the movement characteristics of upper and lower materials. By comparing the joint structure of manipulator, the joint type of manipulator is determined. The D-H parameter model of manipulator is established, and the forward and inverse kinematics of manipulator is analyzed and studied. The correctness of the results is verified by selecting special points. Secondly, the widely used trajectory planning methods are studied: joint interpolation trajectory planning; Cartesian space trajectory planning; Descartes space trajectory planning. It is concluded that the first trajectory planning joint difference curve has limitations and can not guarantee the whole trajectory curve smooth. The second kind of trajectory planning has a large amount of calculation, and it is difficult to guarantee the singularity because the trajectory planning is very intuitive. Relatively speaking, the third kind of trajectory planning can guarantee the continuity of the whole trajectory, and the computation is small. 3) through the above comparative study, B spline curve is selected as the trajectory programming fitting curve. The shortest time is taken as the target, and the global optimization of genetic algorithm is used to search a path with the shortest time. The genetic algorithm is simulated by MATLAB. Finally, the existing ER20-C10 industrial robot is selected to simulate the experiment. The motion time and trajectory of each joint are recorded. The main results are as follows: 1) the spatial pose representation method of manipulator is established. The forward and inverse solutions are obtained, and several trajectory planning methods are compared and studied. (2) through MATILAB simulation, the working time of each segment of the robot is optimized, and the whole joint curve tends to smooth, which verifies the feasibility of the optimization method. The experimental results show that the trajectory planning results obviously reduce the loading and unloading time of the industrial robot and the maximum reduction of 7.3809s.
【学位授予单位】：安徽工程大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM305;TP242

【参考文献】