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

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 plan...

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Bibliographic Details
Published in:Robotics (Basel) Vol. 14; no. 4; p. 48
Main Authors: Chouridis, Ilias, Mansour, Gabriel, Papageorgiou, Vasileios, Mansour, Michel Theodor, Tsagaris, Apostolos
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.04.2025
Subjects:
Aircraft
Algorithms
Artificial intelligence
Barriers
Cloud computing
Collaboration
collaborative robot
Control systems
Health care industry
human and robot collaboration
Industrial applications
Industrial robots
Industrial safety
Industry 4.0
Industry 5.0
Internet of Things
Literature reviews
Manufacturing
Methodology
Methods
Path planning
robot and robot collaboration
Robot arms
robotic arm
Robotics
Robots
Robots, Industrial
Supply chains
Unmanned aerial vehicles
Greece
ISSN:2218-6581, 2218-6581
Online Access:Get full text
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Summary: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.
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ISSN:2218-6581
2218-6581
DOI:10.3390/robotics14040048