Knowledge Sharing and Evolution of Industrial Cloud Robotics

2018 ◽  
Author(s):  
Lixue Jin ◽  
Wenjun Xu ◽  
Zhihao Liu ◽  
Junwei Yan ◽  
Zude Zhou ◽  
...  
Keyword(s):  
Knowledge Sharing ◽  
Resource Sharing ◽  
Industrial Robot ◽  
Cloud Service ◽  
Semantic Knowledge ◽  
Industrial Robots ◽  
Online Data ◽  
Knowledge Evolution ◽  
Cloud Robotics ◽  
Industrial Cloud

Industrial Cloud Robotics (ICR), with the characteristics of resource sharing, lower cost and convenient access, etc., can realize the knowledge interaction and coordination among cloud Robotics (CR) through the knowledge sharing mechanism. However, the current researches mainly focus on the knowledge sharing of service-oriented robots and the knowledge updating of a single robot. The interaction and collaboration among robots in a cloud environment still have challenges, such as the improper updating of knowledge, the inconvenience of online data processing and the inflexibility of sharing mechanism. In addition, the industrial robot (IR) also lacks a well-developed knowledge management framework in order to facilitate the knowledge evolution of industrial robots. In this paper, a knowledge evolution mechanism of ICR based on the approach of knowledge acquisition - interactive sharing - iterative updating is established, and a novel architecture of ICR knowledge sharing is also developed. Moreover, the semantic knowledge in the robot system can encapsulate knowledge of manufacturing tasks, robot model and scheme decision into the cloud manufacturing process. As new manufacturing tasks arrived, the robot platform downloads task-oriented knowledge models from the cloud service platform, and then selects the optimal service composition and updates the cloud knowledge by simulation iterations. Finally, the feasibility and effectiveness of the proposed architecture and approaches are demonstrated through the case studies.

An Efficient Cloud Framework for Multi-Robot System Management

2021 ◽  
Author(s):  
Raihan Kabir ◽  
Yutaka Watanobe ◽  
Keita Nakamura ◽  
Rashedul Islam ◽  
Keitaro Naruse
Keyword(s):  
Data Analysis ◽  
Mobile Robot ◽  
Knowledge Sharing ◽  
Resource Sharing ◽  
Cloud Service ◽  
Management Communication ◽  
Database Model ◽  
Cloud Database ◽  
Cloud Framework ◽  
Multi Robot

Efficient knowledge sharing, computation load minimization, and collision-free movement are very important issues in the field of multi-robot automation. Several cloud robot architectures have been investigated to fulfill these requirements. However, the performance of the cloud-robot architectures created to date are suboptimal due to the lack of efficient data management for multi-robotic systems. With this point in mind, this paper proposes an efficient cloud multi-robot framework with cloud database model for mobile robot applications to facilitate multi-robot management, communication, and resource sharing. In this proposed architecture, the cloud framework is comprised with cloud data analysis, cloud database management, and cloud service management. The data analysis serves different data processing and decision-making tasks for generating the next robot action based on robot sensors’ data with the help of a data access components layer. A multistage cloud database model distributes, stores, and accesses different categories of data related to robot sensors and environments. And cloud service facilitates multi-robot management, communication, and resource sharing in the cloud framework. Additionally, as a use case, a cloud-based convolutional neural network (CNN) model is introduced for learning and recognizing robot application data. The obtained results of our tests indicate that the proposed cloud-robot architecture provides efficient computation power, communications, and knowledge sharing for managing multi-mobile robot systems.

scholarly journals A review on control systems hardware and software for robots of various scale and purpose. Part 1. Industrial robotics

2019 ◽  
Vol 7 (5) ◽  
pp. 30-46 ◽  
Author(s):  
A. M. Romanov
Keyword(s):  
Control System ◽  
Fault Tolerance ◽  
Control Systems ◽  
Intelligent Control ◽  
Industrial Robot ◽  
Cloud Service ◽  
Point Of View ◽  
Industrial Robots ◽  
Robotic Systems ◽  
Industrial Robotics

A review of robotic systems is presented. The paper analyzes applied hardware and software solutions and summarizes the most common block diagrams of control systems. The analysis of approaches to control systems scaling, the use of intelligent control, achieving fault tolerance, reducing the weight and size of control system elements belonging to various classes of robotic systems is carried out. The goal of the review is finding common approaches used in various areas of robotics to build on their basis a uniform methodology for designing scalable intelligent control systems for robots with a given level of fault tolerance on a unified component base. This part is dedicated to industrial robotics. The following conclusions are made: scaling in industrial robotics is achieved through the use of the modular control systems and unification of main components; multiple industrial robot interaction is organized using centralized global planning or the use of previously simulated control programs, eliminating possible collisions in working area; intellectual technologies in industrial robotics are used primarily at the strategic level of the control system which is usually non-real time, and in some cases even implemented as a remote cloud service; from the point of view of ensuring fault tolerance, the industrial robots developers are primarily focused on the early prediction of faults and the planned decommissioning of the robots, and are not on highly-avaliability in case of failures; industrial robotics does not impose serious requirements on the dimensions and weight of the control devices.

Digital Twin-Based Control Approach for Industrial Cloud Robotics

2019 ◽  
Author(s):  
Lan Li ◽  
Wenjun Xu ◽  
Zhihao Liu ◽  
Bitao Yao ◽  
Zude Zhou ◽  
...  
Keyword(s):  
Intelligent Agents ◽  
Effective Means ◽  
Physical World ◽  
Cloud Services ◽  
Industrial Robots ◽  
Control Approach ◽  
Digital Twin ◽  
Digital World ◽  
Cloud Robotics ◽  
Industrial Cloud

Abstract Industrial robots can be mechanical intelligent agents by integrating programs, intelligent algorithms and facilitating intelligent manufacturing models from cyber world into physical entities. After introducing the concept of cloud, their storage, computing, knowledge sharing and evolution capabilities are further strengthened. Digital twin is an effective means to achieve the fusion of physics and information. Therefore, it is feasible to introduce the digital twin to the industrial cloud robotics (ICR), in order to facilitate the control optimization of robots’ running state. The traditional manufacturing task-oriented service composition is limited to execution in the cloud, and it is separated from the underlying robot equipment control, which greatly reduces the real-time performance and accuracy of the underlying service response, such as Robotic Control as a Cloud Service (RCaaCS). Therefore, this paper proposes a digital twin-based control approach for ICR. At the manufacturing cell level, robots’ control instruction service modeling is conducted, and then the control service in the digital world is mapped to the robot action control in the physical world through the concept of digital twin. The accumulated operational data in the physical world can be fed back to the digital world as a reference for simulation and control strategy adjustment, finally achieving the integration of cloud services and robot control. A case study based on workpiece disassembly is presented to verify the availability and effectiveness of the proposed control approach.

Industrial Cloud Robotics Towards Sustainable Manufacturing

2016 ◽  
Author(s):  
Jiayi Liu ◽  
Wenjun Xu ◽  
Jiaqiang Zhang ◽  
Zude Zhou ◽  
Duc Truong Pham
Keyword(s):  
Energy Consumption ◽  
Sustainable Manufacturing ◽  
Industrial Robots ◽  
Production Costs ◽  
Pollutant Emissions ◽  
Actual Problem ◽  
Cloud Robotics ◽  
Stage Of Development ◽  
Energy Consumption Optimization ◽  
Industrial Cloud

Cloud Robotics (CR) is the combination of Cloud Computing and Robotics, which encapsulate resources related with robots as services and is also the robotics’ next stage of development. Under this background, due to the characteristics of convenient access, resource sharing and lower costs, industrial cloud robotics (ICR) is proposed to integrate the industrial robots resources in the worldwide to provide ICR services in worldwide. ICR also plays an important role in improving the productivity of manufacturing. In the manufacturing field, Cloud Manufacturing (CM) and Sustainable Manufacturing (SM) is the developing orientation of future manufacturing industry. The energy consumption optimization of ICR is the crucial issue for manufacturing sustainability. However, currently, ICR systems are not programmed efficiently, which leads to the increase of production costs and pollutant emissions. Thus, it is an actual problem to optimize the energy consumption of ICR. In this paper, in order to achieve the goal of energy consumption optimization in worldwide range, the framework of ICR towards sustainable manufacturing is presented, as well as its enabling methodologies, and it is used to support energy consumption optimization services of ICR in the Cloud environment. This framework can be used to support energy-efficient services related with ICR to realize sustainable manufacturing in the worldwide range.

Cloud robotics: a review of technologies, developments and applications

2017 ◽  
Vol 44 (1) ◽  
pp. 1-5 ◽  
Author(s):  
Robert Bogue
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
Industrial Robots ◽  
Data Sets ◽  
Content Type ◽  
Computing Services ◽  
Cloud Robotics ◽  
Recent Developments ◽  
Potential Benefits ◽  
Insight Into

Purpose This paper aims to provide an insight into the current state of cloud robotics developments, technology and applications. Design/methodology/approach Following a short introduction, this paper first considers the potential benefits of cloud robotics. It discusses cloud service providers and then considers a range of recent applications and developments involving humanoid, mobile and industrial robots. This is followed by details of some recent market entrants and their developments. Finally, brief concluding comments are drawn. Findings Cloud robotics is a rapidly developing technology made possible by the current ubiquitous internet connectivity and the growing number of powerful cloud computing services available. Benefits include access to big data sets, open-source algorithms, code and programmes, massively powerful parallel or grid computing and the sharing of information between robots. The technology has been applied successfully to humanoid, industrial, mobile and other classes of robots, often through direct collaborations between robot manufacturers and major IT companies. Several new companies have been established in very recent years to exploit the capabilities of cloud robotic technologies. Originality/value Cloud robotics is a highly topical and rapidly developing field, and this paper provides a detailed insight into recent developments and applications.

Knowledge Graph-Based Manufacturing Capability Service Optimal Selection for Industrial Cloud Robotics

2020 ◽  
Author(s):  
Yanping Ma ◽  
Wenjun Xu ◽  
Sisi Tian ◽  
Jiayi Liu ◽  
Bitao Yao ◽  
...  
Keyword(s):  
Basic Function ◽  
Industrial Robots ◽  
Robotic Assembly ◽  
Knowledge Graph ◽  
Optimal Selection ◽  
Cloud Robotics ◽  
Manufacturing Capability ◽  
Selection For ◽  
Function Information ◽  
Industrial Cloud

Abstract As an important part of Cloud Manufacturing (CMfg), Industrial Cloud Robotics (ICRs) encapsulates manufacturing capability of physical industrial robots as services for the users. However, a growing number of functionally equivalent services appear in CMfg platform due to the wide use of industrial robots in manufacturing field. It is important to carry out Manufacturing Capability Service (MCS) optimal selection for ICRs from various optional services under CMfg environment. But current service optimal selection method emphasizes on the non-function information of services, and it ignores the interactive relationships between different services and the basic function information of services, which make it difficult to satisfy the various personalized demands of users. Service optimal selection requires the integration and sharing of manufacturing knowledge. Knowledge graph provides an effective way to express and manage knowledge. And it can provide decision support for users to select appropriate ICRs service. Therefore, this paper proposes a method of knowledge graph-based manufacturing capability service optimal selection for ICRs. The function information, association information and non-function information of MCS are described based on knowledge graph. Based on this, the service optimal selection procedure is proposed to realize smart MCS optimal selection for ICRs, which includes feature selection, association selection and user custom weights of non-function indices selection. Finally, a case study based on robotic assembly is presented to demonstrate the effectiveness of proposed method.

SAFETY AND RISK ASSESSMENT AT AUTOMATED WORKPLACE

2018 ◽  
pp. 78-84
Author(s):  
Marek Vagas
Keyword(s):  
Risk Assessment ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Added Value ◽  
Growing Up ◽  
Target Setting ◽  
Clear View ◽  
General Safety

Urgency of the research. Automated workplaces are growing up in present, especially with implementation of industrial robots with feasibility of various dispositions, where safety and risk assessment is considered as most important issues. Target setting. The protection of workers must be at the first place, therefore safety and risk assessment at automated workplaces is most important problematic, which had presented in this article Actual scientific researches and issues analysis. Actual research is much more focused at standard workplaces without industrial robots. So, missing of information from the field of automated workplaces in connection with various dispositions can be considered as added value of article. Uninvestigated parts of general matters defining. Despite to lot of general safety instructions in this area, still is missed clear view only at automated workplace with industrial robots. The research objective. The aim of article is to provide general instructions directly from the field of automated workplaces The statement of basic materials. For success realization of automated workplace is good to have a helping hand and orientation requirements needed for risk assessment at the workplace. Conclusions. The results published in this article increase the awareness and information of such automated workplaces, together with industrial robots. In addition, presented general steps and requirements helps persons for better realization of these types of workplaces, where major role takes an industrial robot. Our proposed solution can be considered as relevant base for risk assessment such workplaces with safety fences or light barriers.

A Polishing Robot Force Control System Based on Time Series Data in Industrial Internet of Things

2021 ◽  
Vol 21 (2) ◽  
pp. 1-22
Author(s):  
Chen Zhang ◽  
Zhuo Tang ◽  
Kenli Li ◽  
Jianzhong Yang ◽  
Li Yang
Keyword(s):  
Time Series ◽  
Control System ◽  
Force Control ◽  
Time Series Data ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Series Data ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Force Control System

Installing a six-dimensional force/torque sensor on an industrial arm for force feedback is a common robotic force control strategy. However, because of the high price of force/torque sensors and the closedness of an industrial robot control system, this method is not convenient for industrial mass production applications. Various types of data generated by industrial robots during the polishing process can be saved, transmitted, and applied, benefiting from the growth of the industrial internet of things (IIoT). Therefore, we propose a constant force control system that combines an industrial robot control system and industrial robot offline programming software for a polishing robot based on IIoT time series data. The system mainly consists of four parts, which can achieve constant force polishing of industrial robots in mass production. (1) Data collection module. Install a six-dimensional force/torque sensor at a manipulator and collect the robot data (current series data, etc.) and sensor data (force/torque series data). (2) Data analysis module. Establish a relationship model based on variant long short-term memory which we propose between current time series data of the polishing manipulator and data of the force sensor. (3) Data prediction module. A large number of sensorless polishing robots of the same type can utilize that model to predict force time series. (4) Trajectory optimization module. The polishing trajectories can be adjusted according to the prediction sequences. The experiments verified that the relational model we proposed has an accurate prediction, small error, and a manipulator taking advantage of this method has a better polishing effect.

scholarly journals Comparative Analysis of the Life-Cycle Cost of Robot Substitution: A Case of Automobile Welding Production in China

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 226
Author(s):  
Xuyang Zhao ◽  
Cisheng Wu ◽  
Duanyong Liu
Keyword(s):  
Life Cycle ◽  
Systems Engineering ◽  
Life Cycle Cost ◽  
Manufacturing Systems ◽  
Large Scale ◽  
Cost Allocation ◽  
Industrial Robot ◽  
Case Analysis ◽  
Industrial Robots ◽  
Analysis Model

Within the context of the large-scale application of industrial robots, methods of analyzing the life-cycle cost (LCC) of industrial robot production have shown considerable developments, but there remains a lack of methods that allow for the examination of robot substitution. Taking inspiration from the symmetry philosophy in manufacturing systems engineering, this article further establishes a comparative LCC analysis model to compare the LCC of the industrial robot production with traditional production at the same time. This model introduces intangible costs (covering idle loss, efficiency loss and defect loss) to supplement the actual costs and comprehensively uses various methods for cost allocation and variable estimation to conduct total cost and the cost efficiency analysis, together with hierarchical decomposition and dynamic comparison. To demonstrate the model, an investigation of a Chinese automobile manufacturer is provided to compare the LCC of welding robot production with that of manual welding production; methods of case analysis and simulation are combined, and a thorough comparison is done with related existing works to show the validity of this framework. In accordance with this study, a simple template is developed to support the decision-making analysis of the application and cost management of industrial robots. In addition, the case analysis and simulations can provide references for enterprises in emerging markets in relation to robot substitution.

Sign in / Sign up

Export Citation Format

Share Document