Digital Twin Driven Four-Dimensional Path Planning of Collaborative Robots for Assembly Tasks in Industry 5.0
Collaborative robots are vital in Industry 5.0 operations. They are utilized to perform tasks in collaboration with humans or other robots to increase overall production efficiency and execute complex tasks. Aiming at a comprehensive approach to assembly processes and highlighting new applications o...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-07-01
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| Series: | Robotics |
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| Online Access: | https://www.mdpi.com/2218-6581/14/7/97 |
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| author | Ilias Chouridis Gabriel Mansour Asterios Chouridis Vasileios Papageorgiou Michel Theodor Mansour Apostolos Tsagaris |
| author_facet | Ilias Chouridis Gabriel Mansour Asterios Chouridis Vasileios Papageorgiou Michel Theodor Mansour Apostolos Tsagaris |
| author_sort | Ilias Chouridis |
| collection | DOAJ |
| description | Collaborative robots are vital in Industry 5.0 operations. They are utilized to perform tasks in collaboration with humans or other robots to increase overall production efficiency and execute complex tasks. Aiming at a comprehensive approach to assembly processes and highlighting new applications of collaborative robots, this paper presents the development of a digital twin (DT) for the design, monitoring, optimization and simulation of robots’ deployment in assembly cells. The DT integrates information from both the physical and virtual worlds to design the trajectory of collaborative robots. The physical information about the industrial environment is replicated within the DT in a computationally efficient way that aligns with the requirements of the path planning algorithm and the DT’s objectives. An enhanced artificial fish swarm algorithm (AFSA) is utilized for the 4D path planning optimization, taking into account dynamic and static obstacles. Finally, the proposed framework is utilized for the examination of a case in which four industrial robotic arms are collaborating for the assembly of an industrial component. |
| format | Article |
| id | doaj-art-998be051a6e048daa1df8b79f50b38ca |
| institution | Kabale University |
| issn | 2218-6581 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Robotics |
| spelling | doaj-art-998be051a6e048daa1df8b79f50b38ca2025-08-20T03:56:46ZengMDPI AGRobotics2218-65812025-07-011479710.3390/robotics14070097Digital Twin Driven Four-Dimensional Path Planning of Collaborative Robots for Assembly Tasks in Industry 5.0Ilias Chouridis0Gabriel Mansour1Asterios Chouridis2Vasileios Papageorgiou3Michel Theodor Mansour4Apostolos Tsagaris5Department of Industrial Engineering and Management, International Hellenic University, 57001 Thessaloniki, GreeceDepartment of Mechanical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, GreeceDepartment of Civil Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, GreeceDepartment of Mechanical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, GreeceDepartment of Mechanical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, GreeceDepartment of Industrial Engineering and Management, International Hellenic University, 57001 Thessaloniki, GreeceCollaborative robots are vital in Industry 5.0 operations. They are utilized to perform tasks in collaboration with humans or other robots to increase overall production efficiency and execute complex tasks. Aiming at a comprehensive approach to assembly processes and highlighting new applications of collaborative robots, this paper presents the development of a digital twin (DT) for the design, monitoring, optimization and simulation of robots’ deployment in assembly cells. The DT integrates information from both the physical and virtual worlds to design the trajectory of collaborative robots. The physical information about the industrial environment is replicated within the DT in a computationally efficient way that aligns with the requirements of the path planning algorithm and the DT’s objectives. An enhanced artificial fish swarm algorithm (AFSA) is utilized for the 4D path planning optimization, taking into account dynamic and static obstacles. Finally, the proposed framework is utilized for the examination of a case in which four industrial robotic arms are collaborating for the assembly of an industrial component.https://www.mdpi.com/2218-6581/14/7/97digital twinassemblycollaborative robotsIndustry 5.0cobotspath planning |
| spellingShingle | Ilias Chouridis Gabriel Mansour Asterios Chouridis Vasileios Papageorgiou Michel Theodor Mansour Apostolos Tsagaris Digital Twin Driven Four-Dimensional Path Planning of Collaborative Robots for Assembly Tasks in Industry 5.0 Robotics digital twin assembly collaborative robots Industry 5.0 cobots path planning |
| title | Digital Twin Driven Four-Dimensional Path Planning of Collaborative Robots for Assembly Tasks in Industry 5.0 |
| title_full | Digital Twin Driven Four-Dimensional Path Planning of Collaborative Robots for Assembly Tasks in Industry 5.0 |
| title_fullStr | Digital Twin Driven Four-Dimensional Path Planning of Collaborative Robots for Assembly Tasks in Industry 5.0 |
| title_full_unstemmed | Digital Twin Driven Four-Dimensional Path Planning of Collaborative Robots for Assembly Tasks in Industry 5.0 |
| title_short | Digital Twin Driven Four-Dimensional Path Planning of Collaborative Robots for Assembly Tasks in Industry 5.0 |
| title_sort | digital twin driven four dimensional path planning of collaborative robots for assembly tasks in industry 5 0 |
| topic | digital twin assembly collaborative robots Industry 5.0 cobots path planning |
| url | https://www.mdpi.com/2218-6581/14/7/97 |
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