基于张拉整体结构的连续型弯曲机械臂设计与研究

为实现对目标物体的缠绕捕获,利用张拉整体结构质量轻、变形大等特点,提出一种基于张拉整体结构的连续型机械臂的设计.本文首先设计连续型机械臂的结构,建立其力学模型.通过准静态和动态分析,对不同驱动形式下的连续型机械臂运动进行仿真,并在实验平台上验证所建力学模型的准确性,最后分析了其工作空间及奇异位姿.实验结果表明本文设计的连续型机械臂可以实现弯曲缠绕变形,满足对不同大小物体进行缠绕捕获的需求.     

断路器柔性装配车间数字孪生系统设计

为优化断路器装配车间的产线结构和作业方法,结合数字孪生技术,提出一种基于多机器人运动控制的断路器柔性自动化车间装配方案。面向自动化装配单元,结合工业机器人的柔性装配工艺及方法,对实体装配车间进行全物理属性的数字化建模,同时建立多机器人的运动学控制模型,将机器人的三维运动模型应用于虚拟孪生场景。通过数据的交互传递,实现物理单元与虚拟单元的实时链接,将车间机器人的运动轨迹、装配状态、作业运送流程等数据信息进行实时显示,从而实现断路器柔性装配数字孪生系统的搭建与同步映射。实验结果证明,所提方案对实现断路器柔性装配有显著效果。     

基于数字孪生的机器人综合实验系统研究

以工业机器人为核心，搭建机器人综合实验系统，通过可编程逻辑控制器（Programmable Logic Controller, PLC）等硬件检测装置，采集设备各项数据。利用OPC UA通信协议，将采集到的信号与数字孪生（Digital Twin）虚拟平台关联起来，实现虚实同步，以实控虚、以虚控实的操作。通过案例研究，实现机器人综合实验系统数字孪生，为机器人工作站设计、仿真、验证、教学等需求提供解决方案。此外，案例的研究为将数字孪生技术切实应用到实际生产开发工作中提供了一个良好的途径。     

连续型机器人运动学仿真和操控系统设计

为了适应越来越复杂的非结构化环境,设计了一种基于球铰链连接和柔性支撑杆结合的线驱动连续型机械臂,并基于常曲率模型的假设建立连续型机器人的运动学模型,研究连续型机器人驱动映射关系,利用MATLAB进行运动学和驱动映射的仿真,仿真结果表明连续型机器人的空间优越性。搭建三关节连续型机器人样机平台,基于连续型机器人的特点设计末端关节跟随手柄操作模式,并在样机平台上实验验证,实验结果表明了运动学模型和驱动映射关系的合理性和正确性以及操控方式的可行性。     

连续型机器人研究综述

连续型机器人是一种新型的仿生机器人,采用“无脊椎”的柔性结构,不具有任何离散关节和刚性连 杆．其弯曲性能优良,对障碍物众多的非结构环境和工作空间狭小的受限工作环境适应能力强,不仅可以像传统机 器人那样在其末端安装执行器以实现抓取和夹持等动作,还可以利用其整个机器人本体实现对物体的抓取．本文对 连续型机器人的仿生原理与结构特点进行了分析,介绍了连续型机器人的研究现状,并对其潜在应用领域和未来研 究工作进行了探讨和展望．     

基于压电陶瓷的柔性机械臂主动振动控制实验研究

柔性机构因其工作效率高,能量消耗低和结构简单等优点被广泛应用于机器人领域.但柔性机构由于刚度较低,易产生弹性振动,使机器人的定位精度和运动精度降低.为了验证在前期的工作中提出的柔性机械臂主动振动最优控制位置分析的正确性,搭建了一个基于Labview的测试系统.在柔性臂上不同位置粘贴压电片来实现对柔性臂不同位置的主动振动控制,通过测试系统得到最优控制位置处和最优控制位置附近的柔性机械臂振动的传感电压,根据控制前后传感电压的变化分析柔性臂抑制的强弱.根据实验结果显示,柔性臂在前三阶振动下,分别在其最优控制位置上获得最高的抑振率,从而验证了最优控制位置的有效性.     

基于数字孪生技术的后勤服务保障平台应用研究

本文基于数字孪生技术,建立统一的园区综合管控模型,研究一种后勤服务保障平台。在分析后勤服务平台系统架构和园区整体数字孪生管控特点的基础上,通过对园区建筑及后勤服务相关的主要管控设备进行三维模型建模,对前端感知设备的统一接入,实现与后勤服务保障相关的业务系统的联动。通过搭建数字孪生技术的后勤服务保障平台,实现园区人、车、物、事件的可视可管可控,通过数字化手段对园区进行精准运营,提升运营管理水平。     

柔性机械臂的变结构振动控制研究

当机械臂的质量很轻,尤其是空间应用场合,机器人系统将受到高度柔性限制并且不可避免地产生机械振动.本文为了证实提出的控制不期望残余振动的方法,设计并建立了柔性机器人实验平台.控制方案采用交流伺服电机通过谐波齿轮减速器驱动柔性机械臂,利用粘贴在柔性臂上的压电陶瓷片(PZT)作为传感器来检测柔性臂的振动.对由于环境激励,尤其是在电机转动(机动)时由于电机力矩产生的振动,采用了几种主动振动控制器包括模态PD控制,软变结构控制(VSC)和增益选择变结构方法,进行柔性臂的振动主动控制实验研究.通过实验比较研究,结果表明采用的控制方法可以快速抑制柔性结构的振动,采用的控制方法是有效的.     

基于张拉整体结构的仿生腿式机器人设计

为提高传统仿生腿式机器人的适应性并简化控制系统,提出了一种基于张拉整体结构的仿生腿式机器人。根据人体腿部的生理结构和运动机理,建立腿部的Snelson X形张拉整体结构等效模型,并通过结构稳定性分析和运动学分析给出了结构刚度匹配方法。通过将旋转和平移运动分离来实现膝关节旋转中心的移动,利用平面四杆机构的死点实现机器人站立时膝关节的锁定;然后通过曲柄滑块机构和位移放大机构实现联动解锁,从而实现人腿行走过程中膝关节的刚-柔转换。最后通过单个电机驱动仿生腿式机器人进行物理样机测试,验证所提结构的有效性和实用性。     

提高柔性冗余度机器人动态特性的最小变形能法

冗余度柔性机器人的运动规划是机器人领域的重要前沿课题之一 .利用此机器人的冗余特性 ,可以改善其运动学和动力学性能 .柔性机器人的变形能能够很好地反映出其整体弹性变形程度 .本文提出了在最小变形能意义下的柔性冗余度机器人运动学规划的新方法 .以平面三柔性臂机器人为例进行了仿真 ,通过与最小末端误差意义下的规划策略进行比较 ,充分显示了最小变形能法在提高柔性机器人动态性能的有效性和优越性     

A Flexible Architecture for Virtual Humans in Networked Collaborative Virtual Environments

Complex virtual human representation provides more natural interaction and communication among participants in networked virtual environments, hence it is expected to increase the sense of being together within the same virtual world. We present a flexible framework for the integration of virtual humans in networked collaborative virtual environments. A modular architecture allows flexible representation and control of the virtual humans, whether they are controlled by a physical user using all sorts of tracking and other devices, or by an intelligent control program turning them into autonomous actors. The modularity of the system allows for fairly easy extensions and integration with new techniques making it interesting also as a testbed for various domains from “classic” VR to psychological experiments. We present results in terms of functionalities, example applications and measurements of performance and network traffic with an increasing number of participants in the simulation.     

数字孪生与生产线仿真技术研究

随着新一代信息技术与制造技术的深度融合,仿真技术正向着信息系统与物理系统深度融合和高效协同的方向发展,应运而生的数字孪生技术成为近年来的新兴研究热点.为探索采用新一代信息技术促进离散制造行业数字化转型升级,从仿真技术的发展脉络和应用场景入手,引入基于数字孪生技术开展生产线仿真分析的研究,介绍了数字孪生技术的概念和内涵,...     

Digital twin-based industrial cloud robotics: Framework,control approach and implementation

Industrial cloud robotics (ICR) integrates cloud computing with industrial robots (IRs). The capabilities of industrial robots can be encapsulated as cloud services and used for ubiquitous manufacturing. Currently, the digital models for process simulation, path simulation, etc. are encapsulated as cloud services. The digital models in the cloud may not reflect the real state of the physical robotic manufacturing systems due to inaccurate or delayed condition update and therefore result in inaccurate simulation and robotic control. Digital twin can be used to realize fine sensing control of the physical manufacturing systems by a combination of high-fidelity digital model and sensory data. In this paper, we propose a framework of digital twin-based industrial cloud robotics (DTICR) for industrial robotic control and its key methodologies. The DTICR is divided into physical IR, digital IR, robotic control services, and digital twin data. First, the robotic control capabilities are encapsulated as Robot Control as-a-Service (RCaaS) based on manufacturing features and feature-level robotic capability model. Then the available RCaaSs are ranked and parsed. After manufacturing process simulation with digital IR models, RCaaSs are mapped to physical robots for robotic control. The digital IR models are connected to the physical robots and updated by sensory data. A case is implemented to demonstrate the workflow of DTICR. The results show that DTICR is capable to synchronize and merge digital IRs and physical IRs effectively. The bidirectional interaction between digital IRs and physical IRs enables fine sensing control of IRs. The proposed DTICR is also flexible and extensible by using ontology models.     

基于数字孪生的虚拟仿真系统研究与应用

为解决全实物平台开发环境搭建困难、不便于测试与维护等问题,在研究PowerPC 处理器的实时嵌入式开发的基础上,采用数字孪生技术的设计思想,完成了一种拥有故障模拟与注入、协同仿真与模块化编程等功能的超实时虚拟仿真系统;提出了一种全数字仿真系统的设计与实现方法,基于数字孪生技术把硬件主板上的处理器以及外围设备虚拟化,集成到数字模型当中;各模型之间相互协同控制,实现CPU控制外部设备与动力学模型等设备之间的通信,以及数据收发、内存读写、串口输出等行为,最终实现与物理设备相同的功能;另外,采用了虚实结合的方法验证了运行结果的准确性,加快了软件执行效率,便于快速全面的系统开发与测试,从而更好地运用到各个领域当中。     

A flexible data schema and system architecture for the virtualization of manufacturing machines (VMM)

Future factories will feature strong integration of physical machines and cyber-enabled software, working seamlessly to improve manufacturing production efficiency. In these digitally enabled and network connected factories, each physical machine on the shop floor can have its ‘virtual twin’ available in cyberspace. This ‘virtual twin’ is populated with data streaming in from the physical machines to represent a near real-time as-is state of the machine in cyberspace. This results in the virtualization of a machine resource to external factory manufacturing systems. This paper describes how streaming data can be stored in a scalable and flexible document schema based database such as MongoDB, a data store that makes up the virtual twin system. We present an architecture, which allows third-party integration of software apps to interface with the virtual manufacturing machines. We evaluate our database schema against query statements and provide examples of how third-party apps can interface with manufacturing machines using the VMM middleware. Finally, we discuss an operating system architecture for VMMs across the manufacturing cyberspace, which necessitates command and control of various virtualized manufacturing machines, opening new possibilities in cyber-physical systems in manufacturing.     

New Paradigm of Data-Driven Smart Customisation through Digital Twin

Big data is one of the most important resources for the promotion of smart customisation. With access to data from multiple sources, manufacturers can provide on-demand and customised products. However, existing research of smart customisation has focused on data generated from the physical world, not virtual models. As physical data is constrained by what has already occurred, it is limited in the identification of new areas to improve customer satisfaction. A new technology called digital twin aims to achieve this integration of physical and virtual entities. Incorporation of digital twin into the paradigm of existing data-driven smart customisation will make the process more responsive, adaptable and predictive. This paper presents a new framework of data-driven smart customisation augmented by digital twin. The new framework aims to facilitate improved collaboration of all stakeholders in the customisation process. A case study of the elevator industry illustrates the efficacy of the proposed framework.     

A framework and method for Human-Robot cooperative safe control based on digital twin

Human-robot collaboration (HRC) combines the robot’s mechanical properties and predictability with human experience, logical thinking, and strain capabilities to alleviate production efficiency. However, ensuring the safety of the HRC process in-real time has become an urgent issue. Digital twin extends functions of virtual models in the design phase of the physical counterpart in the production phase through virtual-real interactive feedback, data fusion analysis, advanced computational features, etc. This paper proposes an HRC safety control framework and corresponding method based on the digital twin. In the design phase, virtual simulation and virtual reality technology are integrated to construct virtual twins of various HRC scenarios for testing and analyzing potential safety hazards. In the production phase, the safety distance between humans and robots of the HRC scene is monitored and calculated by an iterative algorithm according to machine vision and a convolutional neural network. Finally, the virtual twin is driven based on real-scene data, real-time online visual monitoring, and optimization of the HRC’s overall process. A case study using ABB-IRB1600 is presented to verify the feasibility of the proposed approach.     

Progress and prospects of the human–robot collaboration

Recent technological advances in hardware design of the robotic platforms enabled the implementation of various control modalities for improved interactions with humans and unstructured environments. An important application area for the integration of robots with such advanced interaction capabilities is human–robot collaboration. This aspect represents high socio-economic impacts and maintains the sense of purpose of the involved people, as the robots do not completely replace the humans from the work process. The research community’s recent surge of interest in this area has been devoted to the implementation of various methodologies to achieve intuitive and seamless human–robot-environment interactions by incorporating the collaborative partners’ superior capabilities, e.g. human’s cognitive and robot’s physical power generation capacity. In fact, the main purpose of this paper is to review the state-of-the-art on intermediate human–robot interfaces (bi-directional), robot control modalities, system stability, benchmarking and relevant use cases, and to extend views on the required future developments in the realm of human–robot collaboration.     

A digital twin emulator of a modular production system using a data-driven hybrid modeling and simulation approach

Virtual commissioning is a key technology in Industry 4.0 that can address issues faced by engineers during early design phases. The process of virtual commissioning involves the creation of a Digital Twin—a dynamic, virtual representation of a corresponding physical system. The digital twin model can be used for testing and verifying the control system in a simulated virtual environment to achieve rapid set-up and optimization prior to physical commissioning. Additionally, the modular production control systems, can be integrated and tested during or prior to the construction of the physical system. This paper describes the implementation of a digital twin emulator of an automated mechatronic modular production system that is linked with the running programmable logic controllers and allow for exchanging near real-time information with the physical system. The development and deployment of the digital twin emulator involves a novel hybrid simulation- and data-driven modeling approach that combines Discrete Event Simulation and Agent Based Modeling paradigms. The Digital Twin Emulator can support design decisions, test what-if system configurations, verify and validate the actual behavior of the complete system off-line, test realistic reactions, and provide statistics on the system’s performance.