Four-Dimensional Path Planning Methodology for Collaborative Robots Application in Industry 5.0

被引:1
作者
Chouridis, Ilias [1 ]
Mansour, Gabriel [2 ]
Papageorgiou, Vasileios [2 ]
Mansour, Michel Theodor [2 ]
Tsagaris, Apostolos [1 ]
机构
[1] Int Hellenic Univ, Dept Ind Engn & Management, Thessaloniki 57001, Greece
[2] Aristotle Univ Thessaloniki, Dept Mech Engn, Thessaloniki 54124, Greece
关键词
Industry; 5.0; path planning; robotic arm; collaborative robot; human and robot collaboration; robot and robot collaboration; artificial fish swarm algorithm; 4D path planning; artificial intelligence;
D O I
10.3390/robotics14040048
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Industry 5.0 is a developing phase in the evolution of industrialization that aims to reshape the production process by enhancing human creativity through the utilization of automation technologies and machine intelligence. Its central pillar is the collaboration between robots and humans. Path planning is a major challenge in robotics. An offline 4D path planning algorithm is proposed to find the optimal path in an environment with static and dynamic obstacles. The time variable was embodied in an enhanced artificial fish swarm algorithm (AFSA). The proposed methodology considers changes in robot speeds as well as the times at which they occur. This is in order to realistically simulate the conditions that prevail during cooperation between robots and humans in the Industry 5.0 environment. A method for calculating time, including changes in robot speed during path formation, is presented. The safety value of dynamic obstacles, the coefficients of the importance of the terms of the agent's distance to the ending point, and the safety value of dynamic obstacles were introduced in the objective function. The coefficients of obstacle variation and speed variation are also proposed. The proposed methodology is applied to simulated real-world challenges in Industry 5.0 using an industrial robotic arm.
引用
收藏
页数:23
相关论文
共 43 条
[1]   Future of industry 5.0 in society: human-centric solutions, challenges and prospective research areas [J].
Adel, Amr .
JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS, 2022, 11 (01)
[2]   State of Industry 5.0-Analysis and Identification of Current Research Trends [J].
Akundi, Aditya ;
Euresti, Daniel ;
Luna, Sergio ;
Ankobiah, Wilma ;
Lopes, Amit ;
Edinbarough, Immanuel .
APPLIED SYSTEM INNOVATION, 2022, 5 (01)
[3]   Industry 5.0 and Supply Chain Management: Coevolution and Future Research Directions [J].
Bandara, Amila ;
Thibbotuwawa, Amila ;
Perera, H. Niles ;
Nielsen, Peter .
IFAC PAPERSONLINE, 2024, 58 (19) :958-963
[4]   How will the digital twin shape the future of industry 5.0? [J].
Barata, Joao ;
Kayser, Ina .
TECHNOVATION, 2024, 134
[5]   The Future of Healthcare with Industry 5.0: Preliminary Interview-Based Qualitative Analysis [J].
Basulo-Ribeiro, Juliana ;
Teixeira, Leonor .
FUTURE INTERNET, 2024, 16 (03)
[6]  
Bazel Mahmood A., 2024, Advances in Intelligent Computing Techniques and Applications: Intelligent Systems, Intelligent Health Informatics, Intelligent Big Data Analytics and Smart Computing. Lecture Notes on Data Engineering and Communications Technologies (211), P274, DOI 10.1007/978-3-031-59707-7_24
[7]  
Boudouaia Mohammed Amine, 2024, 2024 21st Learning and Technology Conference (L&T), P203, DOI 10.1109/LT60077.2024.10469476
[8]  
Chander B., 2022, Artificial intelligence-based internet of things systems, P3, DOI DOI 10.1007/978-3-030-87059-11
[9]   2D multi-area coverage path planning using L-SHADE in simulated ocean survey [J].
Chen, Guanzhong ;
Shen, Yue ;
Zhang, Yixiao ;
Zhang, Wenfeng ;
Wang, Dianrui ;
He, Bo .
APPLIED SOFT COMPUTING, 2021, 112
[10]   Enhanced Hybrid Artificial Fish Swarm Algorithm for Three-Dimensional Path Planning Applied to Robotic Systems [J].
Chouridis, Ilias ;
Mansour, Gabriel ;
Papageorgiou, Vasileios ;
Mansour, Michel Theodor ;
Tsagaris, Apostolos .
ROBOTICS, 2025, 14 (03)