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AI-Based Design of a Parallel Robot Used as a Laser Tracker System: Intelligent vs. Nonlinear Classical Controllers

机译:基于AI的并行机器人用作激光跟踪器系统的设计:智能与非线性经典控制器

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Classical ways for coordinate measuring devices are manual theodolites, photogrammetry-based systems, total stations and a recently-introduced device referred to as laser tracker systems. Basically, a laser tracker system is a more accurate and reliable 3D measurement tool that allows to increase and maintain accuracy as time goes by. Laser tracker systems deals with industry-based measuring problems which can be alignment, reverse engineering, tool building, part inspection, installation, and manufacturing and assembly integration. A very interesting case of the latter is robot-tracking calibration in an welding line. In a welding line, robots are controlled in order to keep a prescribed trajectory to accomplish its welding task properly. Nevertheless, in spite of a good control algorithm design, as time goes by, deviations appear and some maintenance has to be done on the robotic unit. So, robot calibration can be done with a laser tracker. Although laser tracker systems are made by very well established and serious companies, their laser products may be very expensive for small or medium size industries. Our contribution is to offer a parallel robot-based laser tracker system model whose implementation would result cheaper than sophisticated laser devices and takes advantage of the parallel robot bondages as high payload. As a first step, simulations of the controlled systems are done here. This parallel robot-based laser tracker is designed to help in the calibration process which consists in repeating some specified trajectory for the serial (welding) robot. The laser tracker system tracks the welding robot trajectory in a day-by-day period of time (for instance) in order to identify the moment when a deviation of the reference trajectory happens. Hence, corrections can be done avoiding greater problems in the welding line. In order to design the parallel robot-based tracker system, a kinematic analysis and a dynamical modeling have to be done in order to design a set of controllers which will be assessed. All of it assisted by AI (artificial intelligence) algorithms. The laser tracker kinematic analysis was done assisted by ANN (artificial neural networks) and by GA (genetic algorithms). This fact allowed to compute numerically/graphically the laser tracker workspace in order to warrant the right accessibility of the corresponding 3D (three dimensional) space. A dynamical model which represents the parallel robot-based laser tracker system was also obtained. This model was used by our set of controllers. The controller design is split into two groups: One considers AI-based algorithms and the second one, classical design-based controllers. A comparison between the two groups is done and advantages/disadvantages are shown in terms of performance in the presence of a persistent perturbation which models ground vibrations in the factory the welding robots are. Such vibrations are endlessly present because they are produced by other assembling machines which disturb the welding process. So, in spite of this perturbation our parallel robot-based laser tracker system showed to behave well with Intelligent Control keeping good tracking of a sinusoidal welding calibration trajectory in the serial robot. In this work it is assumed that a laser device is mounted in the parallel robot with inertial dynamical effect on the parallel robot. Analytical developments are provided as well as numerical/graphical solutions done in MATLAB/SIMULINK to deal with this complex dynamical system. An integral viewpoint with ANN, GA, and Fuzzy Logic was used in this study.
机译:坐标测量设备的经典方法是手动经纬仪,基于摄影测量的系统,全站仪和最近推出的称为激光跟踪器系统的设备。基本上,激光跟踪器系统是一种更准确,更可靠的3D测量工具,可以随着时间的流逝提高并保持准确性。激光跟踪仪系统处理基于行业的测量问题,这些问题可能包括对准,反向工程,工具制造,零件检查,安装以及制造和装配集成。后者的一个非常有趣的案例是焊接线中的机器人跟踪校准。在焊接生产线中,控制机器人以保持规定的轨迹以正确完成其焊接任务。尽管如此,尽管设计了良好的控制算法,但随着时间的流逝,仍会出现偏差,并且必须对机器人单元进行一些维护。因此,可以使用激光跟踪仪进行机器人校准。尽管激光跟踪系统是由非常成熟和认真的公司制造的,但其激光产品对于中小型行业而言可能会非常昂贵。我们的贡献是提供一个基于并行机器人的激光跟踪器系统模型,该模型的实现将比复杂的激光设备便宜,并利用并行机器人的束缚作为高负载。第一步,在此对受控系统进行仿真。这种基于机器人的并行激光跟踪仪旨在帮助校准过程,该过程包括为串行(焊接)机器人重复一些指定的轨迹。激光跟踪器系统每天(例如)跟踪焊接机器人的轨迹,以识别参考轨迹发生偏差的时刻。因此,可以进行校正以避免在焊接线中出现更大的问题。为了设计基于机器人的并行跟踪器系统,必须进行运动学分析和动力学建模,以设计将要评估的一组控制器。所有这些都由AI(人工智能)算法辅助。激光跟踪器的运动学分析是在ANN(人工神经网络)和GA(遗传算法)的协助下完成的。这一事实允许以数字/图形方式计算激光跟踪器工作空间,以保证相应3D(三维)空间的正确可访问性。还获得了代表基于并行机器人的激光跟踪器系统的动力学模型。我们的控制器使用了此模型。控制器设计分为两组:一组考虑基于AI的算法,第二组考虑基于经典设计的控制器。进行了两组之间的比较,并在持续扰动的情况下在性能方面显示了优点/缺点,该扰动模拟了焊接机器人所在工厂的地面振动。这种振动无休止地存在,因为它们是由其他组装机器产生的,这些组装机器会干扰焊接过程。因此,尽管有这种干扰,我们的基于并行机器人的激光跟踪器系统仍表现出良好的性能,而智能控制系统可以在串行机器人中保持对正弦焊接校准轨迹的良好跟踪。在这项工作中,假设将激光设备安装在并联机器人中,并且对并联机器人具有惯性动力作用。提供了分析开发以及在MATLAB / SIMULINK中完成的数值/图形解决方案,以处理这个复杂的动力学系统。在这项研究中使用了具有ANN,GA和模糊逻辑的积分观点。

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