Knowledge-Based Digital Twin for Predicting Interactions in Human-Robot Collaboration

2021 ◽  
Author(s):  
Tadele Belay Tuli ◽  
Linus Kohl ◽  
Sisay Adugna Chala ◽  
Martin Manns ◽  
Fazel Ansari
Keyword(s):  
Digital Twin ◽  
Knowledge Based ◽  
Human Robot Collaboration

scholarly journals Semantic knowledge based reasoning framework for human robot collaboration

Procedia CIRP ◽  
2021 ◽  
Vol 97 ◽  
pp. 373-378
Author(s):  
Sharath Chandra Akkaladevi ◽  
Matthias Plasch ◽  
Michael Hofmann ◽  
Andreas Pichler
Keyword(s):  
Semantic Knowledge ◽  
Knowledge Based ◽  
Human Robot Collaboration

Knowledge Recommendation System for Human-Robot Collaborative Disassembly Using Knowledge Graph

2021 ◽  
Author(s):  
Yang Hu ◽  
Yiwen Ding ◽  
Feng Xu ◽  
Jiayi Liu ◽  
Wenjun Xu ◽  
...  
Keyword(s):  
Recommendation System ◽  
Industrial Robots ◽  
Knowledge Graph ◽  
Disassembly Process ◽  
Knowledge Based ◽  
Manufacturing Efficiency ◽  
Human Operators ◽  
Traditional Manufacturing ◽  
Human Robot Collaboration

Abstract In recent years, more and more attention has been paid to Human-Robot Collaborative Disassembly (HRCD) in the field of industrial remanufacturing. Compared with the traditional manufacturing, HRCD helps to improve the manufacturing flexibility with considering the manufacturing efficiency. In HRCD, knowledge could be obtained from the disassembly process and then provides useful information for the operator and robots to execute their disassembly tasks. Afterwards, a crucial point is to establish a knowledge-based system to facilitate the interaction between human operators and industrial robots. In this context, a knowledge recommendation system based on knowledge graph is proposed to effectively support Human-Robot Collaboration (HRC) in disassembly. A disassembly knowledge graph is constructed to organize and manage the knowledge in the process of HRCD. After that, based on this, a knowledge recommendation procedure is proposed to recommend disassembly knowledge for the operator. Finally, the case study demonstrates that the developed system can effectively acquire, manage and visualize the related knowledge of HRCD, and then assist the human operator to complete the disassembly task by knowledge recommendation, thus improving the efficiency of collaborative disassembly. This system could be used in the human-robot collaboration disassembly process for the operators to provide convenient knowledge recommendation service.

An integrated mixed reality system for safety-aware human-robot collaboration using deep learning and digital twin generation

2022 ◽  
Vol 73 ◽  
pp. 102258
Author(s):  
Sung Ho Choi ◽  
Kyeong-Beom Park ◽  
Dong Hyeon Roh ◽  
Jae Yeol Lee ◽  
Mustafa Mohammed ◽  
...  
Keyword(s):  
Deep Learning ◽  
Mixed Reality ◽  
Digital Twin ◽  
Human Robot Collaboration

scholarly journals Digital Twin-Driven Human Robot Collaboration Using a Digital Human

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8266
Author(s):  
Tsubasa Maruyama ◽  
Toshio Ueshiba ◽  
Mitsunori Tada ◽  
Haruki Toda ◽  
Yui Endo ◽  
...  
Keyword(s):  
Flexible Manufacturing ◽  
Production Management ◽  
Dynamic Scheduling ◽  
Production Systems ◽  
Physical Load ◽  
Real Time Control ◽  
Digital Twin ◽  
Time Control ◽  
Digital Human ◽  
Human Robot Collaboration

Advances are being made in applying digital twin (DT) and human–robot collaboration (HRC) to industrial fields for safe, effective, and flexible manufacturing. Using a DT for human modeling and simulation enables ergonomic assessment during working. In this study, a DT-driven HRC system was developed that measures the motions of a worker and simulates the working progress and physical load based on digital human (DH) technology. The proposed system contains virtual robot, DH, and production management modules that are integrated seamlessly via wireless communication. The virtual robot module contains the robot operating system and enables real-time control of the robot based on simulations in a virtual environment. The DH module measures and simulates the worker’s motion, behavior, and physical load. The production management module performs dynamic scheduling based on the predicted working progress under ergonomic constraints. The proposed system was applied to a parts-picking scenario, and its effectiveness was evaluated in terms of work monitoring, progress prediction, dynamic scheduling, and ergonomic assessment. This study demonstrates a proof-of-concept for introducing DH technology into DT-driven HRC for human-centered production systems.

scholarly journals A knowledge-based approach to the layout optimization of human–robot collaborative workplace

2020 ◽  
Author(s):  
A. Rega ◽  
F. Vitolo ◽  
C. Di Marino ◽  
S. Patalano
Keyword(s):  
Production Systems ◽  
Industrial Robot ◽  
Safety Standards ◽  
Knowledge Based ◽  
Standards Compliance ◽  
Main Challenge ◽  
Flexible Production Systems ◽  
Robot Systems ◽  
Human Robot Collaboration ◽  
Collaborative Robot

Abstract Human–robot collaboration (HRC) solutions are replacing classic industrial robot due to the possibility of realizing more flexible production systems. Collaborative robot systems, named cobot, can work side by side with humans combining their strengths. However, obtaining an efficient HRC is not trivial; indeed, the potential advantages of the collaborative robotics increase as complexity increases. In this context, the main challenge is to design the layout of collaborative workplaces facing the facility layout problem and ensuring the safety of the human being. To move through the high number of safety standards could be very tiring and unproductive. Therefore, in this work a list of key elements, linked to reference norms and production needs, characterizing the collaborative workplace has been identified. Then, a graph-based approach has been used in order to organize and easily manage this information. The management by means graphs has facilitated the implementation of the acquired knowledge in a code, developed in Matlab environment. This code aims to help the designer in the layout organization of human–robot collaborative workplaces in standards compliance. The paper presents the optimization code, named Smart Positioner, and the operation is explained through a workflow diagram.

scholarly journals Collaborative Workplace Design: A Knowledge-Based Approach to Promote Human–Robot Collaboration and Multi-Objective Layout Optimization

2021 ◽  
Vol 11 (24) ◽  
pp. 12147
Author(s):  
Andrea Rega ◽  
Castrese Di Marino ◽  
Agnese Pasquariello ◽  
Ferdinando Vitolo ◽  
Stanislao Patalano ◽  
...  
Keyword(s):  
Complex Problem ◽  
Optimization Criterion ◽  
Layout Design ◽  
Industrial Case Study ◽  
Manufacturing Plants ◽  
Knowledge Based ◽  
Control Factors ◽  
Modeling Paradigm ◽  
Human Robot Collaboration

The innovation-driven Industry 5.0 leads us to consider humanity in a prominent position as the center of the manufacturing field even more than Industry 4.0. This pushes us towards the hybridization of manufacturing plants promoting a full collaboration between humans and robots. However, there are currently very few workplaces where effective Human–Robot Collaboration takes place. Layout designing plays a key role in assuring safe and efficient Human–Robot Collaboration. The layout design, especially in the context of collaborative robotics, is a complex problem to face, since it is related to safety, ergonomics, and productivity aspects. In the current work, a Knowledge-Based Approach (KBA) is adopted to face the complexity of the layout design problem. The framework resulting from the KBA allows for developing a modeling paradigm that enables us to define a streamlined approach for the layout design. The proposed approach allows for placing resource within the workplace according to a defined optimization criterion, and also ensures compliance with various standards. This approach is applied to an industrial case study in order to prove its feasibility. A what-if analysis is performed by applying the proposed approach. Changing three control factors (i.e., minimum distance, robot speed, logistic space configuration) on three levels, in a Design of Experiments, 27 layout configurations of the same workplace are generated. Consequently, the inputs that most affect the layout design are identified by means of an Analysis of Variance (ANOVA). The results show that only one layout is eligible to be the best configuration, and only two out of three control factors are very significant for the designing of the HRC workplace layout. Hence, the proposed approach enables the designing of standard compliant and optimized HRC workplace layouts. Therefore, several alternatives of the layout for the same workplace can be easily generated and investigated in a systematic manner.

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