移动焊接机器人的轨迹规划与跟踪控制

发布时间：2018-01-31 03:03

本文关键词： 移动焊接机器人焊缝识别轨迹规划跟踪控制滑模变结构控制　出处：《南京理工大学》2017年硕士论文　论文类型：学位论文

【摘要】：随着工业4.0的提出和《中国制造2025》的颁布,我国工业生产朝着自动化,智能化、信息化方向发展已经成为必然的趋势。焊接机器人融合了识别、焊接、控制等众多技术,反应了一个国家的科技水平。本文以移动焊接机器人为研究对象,主要研究了焊缝识别算法、移动焊接机器人运动学与动力学模型、轨迹规划和跟踪控制的方法。1焊缝识别算法采用中值滤波和均值滤波算法对焊缝及周边的图像进行处理,削弱干扰,并采用Sobel边缘检测算法提取焊缝的边缘曲线,从而达到焊缝识别的目的。2运动学与动力学模型首先分析了移动平台的非完整性,并采用奇次变换的方法建立移动平台的运动模型。然后采用Denavit-Hartenberg建模方法建立了机械臂的运动学模型。然后结合移动平台和机械臂的运动模型建立了焊接机器人的运动学模型,最后采用拉格朗日力学法建立了移动焊接机器人的动力学方程。3轨迹规划首先假设移动平台做直线运动,研究了机械臂的轨迹规划问题。采用梯度下降法与二分法结合的算法对机械臂的关节轨迹进行优化,并通过仿真验证了算法的有效性。然后针对大曲度焊缝,研究了移动平台和机械臂的同步规划问题。针对同步规划问题,首先研究了机械臂末端位置点到点的规划问题,通过分析机械臂末端点到点的运动特点总结出规划任务的实质是选择移动平台运动所围绕圆心的位置,并采用基于梯度下降法与二分法结合的优化算法对移动平台轮子和机械臂的关节运动进行了规划,仿真结果显示机械臂的末端较好的跟踪离散化后焊缝轨迹上的点。然后研究了机械臂末端的速度规划问题,采用遗传算法规划移动平台左右轮的角速度和机械臂的关节速度曲线,使得机械臂的末端速度方向与焊缝的切线方向保持一致,从而实现机械臂末端跟踪焊缝轨迹。通过仿真验证规划方法的有效性。4基于滑模变结构控制的移动焊接机器人控制器研究首先设计了移动焊接机器人的线性滑模切换面。然后在移动焊接机器人的动力学方程的基础上设计了基于指数趋近律的控制律,并采用饱和函数削弱滑模变结构控制的抖振。最后采用S函数在Simulink中搭建了滑模控制器和移动焊接机器人的动力学模型。通过仿真验证了滑模控制器的有效性,不仅削弱了抖振现象,而且提高了系统的鲁棒性和轨迹跟踪的效果。
[Abstract]:With the introduction of industry 4.0 and the promulgation of "made in China 2025", the development of China's industrial production towards automation, intelligence and information has become an inevitable trend. Welding robot fusion recognition. Welding, control and many other technologies reflect the scientific and technological level of a country. In this paper, the mobile welding robot as the research object, mainly studied the weld identification algorithm, kinematics and dynamics model of mobile welding robot. Methods of trajectory Planning and tracking Control. 1. The median filter and mean filter algorithm are used to process the images of the weld seam and its periphery, so as to reduce the interference. The Sobel edge detection algorithm is used to extract the edge curve of the weld seam. 2. The kinematics and dynamics model is used to analyze the non-integrity of the mobile platform. The motion model of mobile platform is established by odd degree transformation, and then the kinematics model of manipulator is established by using Denavit-Hartenberg modeling method. The kinematics model of welding robot is established. Finally, the dynamic equation .3 trajectory planning of mobile welding robot is established by using Lagrange mechanics method. Firstly, the linear motion of mobile platform is assumed. The trajectory planning problem of the manipulator is studied. The joint trajectory of the manipulator is optimized by using gradient descent method and dichotomy, and the effectiveness of the algorithm is verified by simulation. The synchronization planning problem of mobile platform and manipulator is studied. Aiming at the synchronization planning problem, the point to point planning of the end of the manipulator is first studied. By analyzing the motion characteristics of the end point to point of the manipulator, it is concluded that the essence of the planning task is to select the position around the center of the motion of the mobile platform. An optimization algorithm based on gradient descent and dichotomy is used to plan the joint motion of the wheel and manipulator of the mobile platform. The simulation results show that the end of the manipulator can track the points on the weld trajectory after discretization. Then the velocity planning problem of the end of the manipulator is studied. Genetic algorithm is used to plan the angular velocity of the left and right wheels of the mobile platform and the joint velocity curve of the manipulator, so that the direction of the end velocity of the manipulator is consistent with the tangent direction of the weld. The effectiveness of the planning method is verified by simulation. 4. The research of mobile welding robot controller based on sliding mode variable structure control. Firstly, the linear slip of mobile welding robot is designed. Then the control law based on exponential approach law is designed based on the dynamic equation of mobile welding robot. Finally, the dynamic models of sliding mode controller and mobile welding robot are built by S function in Simulink. The sliding mode control is verified by simulation. The effectiveness of the machine. Not only the chattering phenomenon is weakened, but also the robustness of the system and the effect of trajectory tracking are improved.
【学位授予单位】：南京理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242

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