BOSCH伺服控制系统在ZJ19B卷接机组中的应用

介绍BOSCH伺服控制系统成功应用于ZJ19B卷接机组传动系统中,使机器供丝、供纸、刀头、嘴机部分各个电机的运行更加稳定,控制精度显著提高;减少因控制精度不够而引起的非正常停机次数,提高机器的有效作业率,节约原料;同时使烟支的重量、圆周、紧头等各项指标合格率显著提高。     

贝加莱ACOPOSmulti在奇瑞6关节机器人控制系统中的应用

本文关于贝加莱ACOPOSmulti伺服系统和机器人软件库在奇瑞6关节机器人研发中的应用。介绍了机器人机械系统的组成和性能参数,重点描述了以APC820工控机和ACOPOSmuhi伺服驱动器为核心。基于EthernetPOWERLINK工业实时以太网和AutomationStudio集成软件开发平台的机器人控制系统,并讨论了通过MATLAB／Simulink的代码自动生成技术、ACOPOSmuhi驱动系统的负载惯量前馈技术等关键技术环节。     

基于计算的工业喷涂机器人基本参数设计方法

设计与确定机器人参数需要在各项性能之间进行折衷,常常是一个耗时的迭代过程。本文提出了一种工业喷涂机器人基本参数确定的一般方法。通过喷涂机器人的设计与开发过程,基于机器人建模方法,归纳出机器人基本参数对各项性能尤其是工作空间特性的影响因素与规律,并在此过程中上分析了其结构参数对机器人工作空间和性能的影响,从而得出了机器人工作空间特性与结构参数之间的内在联系,为工业机器人的设计提供依据。     

Robust pole assignment for incomplete nonlinear decoupling applied to robots

A robustness analysis and synthesis for incomplete nonlinear decoupling for a class of nonlinear systems is discussed. Rigid and elastic-joint robot models belong to this class. For the elastic case, a transformation facilitates the robustness analysis under a weak assumption. Charts with H ₁- and H - norms of closed-loop disturbance transfer functions of the nonlinear-decoupled system are presented for a robust pole assignment.     

自动化学科面临的挑战

本文分析了控制理论与应用、模式识别与智能系统、导航制导与控制、系统科学与工程、人工智能与自动化交叉等领域的发展现状. 结合科技发展、国内国际研究前沿和新兴领域对自动化科学技术的需求, 提出重点发展智能控制理论和方法、高性能作业机器人、信息物理系统、导航与控制技术、重大装备自动化技术、自主智能系统和人工智能驱动的自动化技术优先领域, 加强数据驱动控制理论、人工智能基础理论研究, 进一步发展人机协同、跨域融合的智能自动化, 为实现国家社会的全面信息化智能化提供理论和技术保障.     

Introducing autonomous aerial robots in industrial manufacturing

Although ground robots have been successfully used for many years in manufacturing, the capability of aerial robots to agilely navigate in the often sparse and static upper part of factories makes them suitable for performing tasks of interest in many industrial sectors. This paper presents the design, development, and validation of a fully autonomous aerial robotic system for manufacturing industries. It includes modules for accurate pose estimation without using a Global Navigation Satellite System (GNSS), autonomous navigation, radio-based localization, and obstacle avoidance, among others, providing a fully onboard solution capable of autonomously performing complex tasks in dynamic indoor environments in which all necessary sensors, electronics, and processing are on the robot. It was developed to fulfill two use cases relevant in many industries: light object logistics and missing tool search. The presented robotic system, functionalities, and use cases have been extensively validated with Technology Readiness Level 7 (TRL-7) in the Centro Bahía de Cádiz (CBC) Airbus D&S factory in fully working conditions.     

Safe and intuitive manual guidance of a robot manipulator using adaptive admittance control towards robot agility

Key areas of robot agility include methods that increase capability and flexibility of industrial robots and facilitate robot re-tasking. Manual guidance can achieve robot agility effectively, provided that a safe and smooth interaction is guaranteed when the user exerts an external force on the end effector. We approach this by designing an adaptive admittance law that can adjust its parameters to modify the robot compliance in critical areas of the workspace, such as near and on configuration singularities, joint limits, and workspace limits, for a smooth and safe operation. Experimental validation was done with two tests: a constraint activation test and a 3D shape tracing task. In the first one, we validate the proper response to constraints and in the second one, we compare the proposed approach with different admittance parameter tuning strategies using a drawing task where the user is asked to guide the robot to trace a 3D profile with an accuracy or speed directive and evaluate performance considering path length error and execution time as metrics, and a questionnaire for user perception. Results show that appropriate response to individual and simultaneous activation of the aforementioned constraints for a safe and intuitive manual guidance interaction is achieved and that the proposed parameter tuning strategy has better performance in terms of accuracy, execution time, and subjective evaluation of users.     

基于多传感器信息融合技术在灭火机器人系统的设计

提出一种通过多传感器信息融合技术来提高灭火机器人的火焰、距离检测的准确性,设计了由超声波、红外测距模块和数据融合模块组成的测距避障子系统;由红外火焰检测模块、数据融合模块组成的火焰检测子系统,在此基础上,采用自适应加权数据融合算法分别对多传感器检测的距离和火焰信息进行融合,以提高对火源目标判断的准确度;实验结果表明,设计的智能灭火机器人传感器软硬件系统测量相对误差小,能很好的反映火灾现场信息,满足火情探测和灭火需要,具有很强的使用价值。     

基于非线性PID的柔性两轮机器人运动控制

柔性两轮机器人是一种不稳定、非线性、强耦合系统。该系统的突出特点是在机器人的腰部装有柔性的机体结构,能够更好地模拟人和动物的生物动力学特性,具有更好的仿生性质,同时,系统的控制难度显著增大,为使机器人能够平衡直立运动,且具有较强的鲁棒性,提出了非线性PD的姿态平衡控制方法,实现了机器人的姿态平衡,并同时设计了PID航向差动控制结构驱动左右轮电机,使机器人能够完成直线行进、自旋、环绕等多种运动平衡模式。实验结果表明,机器人具有优良的平衡能力和机动性能,从而验证了方法的有效性。     

基于机器人运动模型的EKF-SLAM算法改进

针对两轮驱动机器人运动模型定向误差的累积问题,提出改进的三轮驱动机器人运动模型,对EKF-SLAM算法的一致性进行改进;该模型通过对机器人车轮线速度的解耦运算,将机器人运动过程中的旋转角速度提取出来并作为系统的控制输入之一,从而可以直接得到各个控制时间间隔内的机器人姿态角变化,很好地避免了机器人定向误差的累积;最后,基于归一化估计方差的检验标准进行实验,验证了三轮驱动机器人运动模型有效提高了EKF-SLAM算法的一致性。