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。     

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.     

Examining joint loading and self-reported exertion and discomfort during ladder handling

Ladder handling by telecommunications technicians represents an indispensable part of their daily work, but may generate musculoskeletal injury risk. These workers have a high prevalence of shoulder and back injuries, motivating research to quantify postures and loading using different ladders during common handling tasks. Twenty-five participants completed carry, raise (against a wall or free standing), and simulated removal from a van roof tasks using three ladders (8.5m 2-piece wood; 8.5m 2-piece fibreglass, 9.2m 3-piece wood). Data collection included kinematics and kinetics during these ladder handling tasks, as well as perceived discomfort, perceived exertion and post-collection ladder and task preferences. Significant effects depended on task and ladder. Dominant arm (the arm completing the primary action) elevation was higher while extending the ladder (114.7 ± 3.4°) than the carry task (53.5 ± 3.5°) (p < 0.05). Joint moments in the dominant shoulder and trunk were highest for the 2-piece wood ladder (59.0 ± 2.2 Nm and 254.8 ± 8.8 Nm) averaged across all tasks. Joint forces were increased when using the 2-piece wood ladder compared to the 3-piece wood ladder (p < 0.05), while the greatest discomfort in the shoulders occurred using the 2-piece wood ladder in the carry task. Many tasks approached or exceeded strength capability of a 50th percentile male's predicted strength. While no ladder universally mitigated physical demands while lowering perceptual difficulty, construction differences yielded trends toward preferring the 2-piece fibreglass or 3-piece wood ladders over the 2-piece wood ladder. This work has direct relevance to workplaces with ladder handling and provides recommendations for ladder selection and strength requirements across tasks.     

Modeling and implementation of a digital twin of material flows based on physics simulation

Cyber-physical production systems enable adaptivity and flexibility when manufacturing customized products in small batches. Due to varying routes and a high variance of workpieces, material flows in cyber-physical production systems can get highly complex, which can lead to physically induced disturbances that can result in accidents or decreased throughput and high costs. This issue can be addressed by applying a physics engine to simulate the physical interaction between workpieces and the material handling systems during the operation. Connecting such a digital model to a real material handling system in order to derive simulation-based decision support leads to the concept of digital twins. To date, few practical implementations of digital twins in manufacturing outside the machine tool domain were reported. Therefore, this paper describes the modeling and the subsequent implementation of an integrated system that consists of a real material handling system and its digital twin, based on physics simulation. A practical use case demonstrates the versatile advantages of the implemented solution for a manufacturing system with respect to the three digital twin functions prediction, monitoring and diagnosis.     

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。     

以ARM为核心的嵌入式体感遥控器设计

介绍一种以ARM为核心的嵌入式服务机器人体感遥控器的设计。硬件上,本遥控器采用具有ARM Cortex—M3内核的STM32F103C8T6作为核心处理器,选用ST公司的iNEMO惯性导航模块进行手部姿态的识别,同时还具有LCD显示模块、无线收发模块和电源模块;软件上,采用嵌入式操作系统μC／OS—Ⅱ实现多任务的调度和外围设备的管理。经实验验证,本遥控器具有高稳定性、高实时性、高可靠性、低误码率等优点。     

Design of robotic visual servo control based on neural network and genetic algorithm

A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation (BP) neural network is used to make a direct transition from image feature to joint angles without requiring robot kinematics and camera calibration. To speed up the convergence and avoid local minimum of the neural network, this paper uses a genetic algorithm to find the optimal initial weights and thresholds and then uses the BP algorithm to train the neural network according to the data given. The proposed method can effectively combine the good global searching ability of genetic algorithms with the accurate local searching feature of BP neural network. The Simulink model for PUMA560 robot visual servo system based on the improved BP neural network is built with the Robotics Toolbox of Matlab. The simulation results indicate that the proposed method can accelerate convergence of the image errors and provide a simple and effective way of robot control.