一种基于数据竞争的高分辨率图像的聚类分割算法

近些年,机器人技术得到了迅猛的发展,应用越来越广泛.随着机器人技术的推广和普及,对机器人使用的要求也越来越高,其中对智能机器人的要求尤显迫切.机器视觉是智能机器人研究领域的一个重要研究方向.在机器人视觉系统中,核心问题是目标提取,对目标实时、准确、快速提取的关键技术是图像分割.由于机器人感知的环境的复杂性及目标的多样性,往往导致机器人感知获得的图像数据量较大且图像本身存在不可预知的复杂性,这就对准确的目标分割和提取处理提出了挑战性问题.本文针对高分辨率图像数据集的分割处理,提出一种新的聚类算法,即根据数据点能量和的大小识别类代表点和类成员点,通过数据点间的竞争识别出最有能力成为簇成员的数据点,并将其与mean shift聚类算法有效地结合应用于彩色图像分割问题中,能够快速高效地实现高分辨率图像的目标分割,并得到较好的图像分割效果.实验结果表明,本文算法在分割效果和分割效率上明显优于传统聚类算法.     

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。     

关于新建炉EDTA低浓度清洗的探讨

阐述了EDTA清洗锅炉的基本原理,低浓度清洗新建炉的工艺、方法及控制要点,EDTA低浓度清洗与协调EDTA清洗的经济性比较,为新建炉EDTA低浓度清洗探索了方向。     

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。     

RFID复杂事件处理关键技术的研究与改进

RFID复杂事件处理是一个新兴的技术领域,它用来处理大量的简单事件,并从中整理出有价值的事件。RFID事件和传统的事件相比较具有海量性、空间性和时间性、数据不准确性等特征。文中在分析RFID数据特点的基础上,对RFID复杂事件处理的关键技术进行研究和改进,主要介绍RFID数据的清洗和事件检测技术。对于RFID数据清洗部分,提出了多层次过滤的方法使得到的数据更接近真实情况,而事件检测方面则提出了局部检测和全局检测相结合的方法对相关数据进行检测以得到更有意义的数据供上层应用使用。最后,对RFID复杂事件处理的发展趋势做出展望。     

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.