Multi-Objective Immune Optimization of Path Planning for Ship Welding Robot
In order to improve the welding efficiency of the ship welding robot, the path planning of the welding robot based on immune optimization is proposed by taking the welding path length and energy loss as the optimization goals. First, on the basis of the definition of the path planning of the welding...
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| Vydané v: | Electronics (Basel) Ročník 12; číslo 9; s. 2040 |
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| Hlavní autori: | , , , , |
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| Jazyk: | English |
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MDPI AG
28.04.2023
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| ISSN: | 2079-9292, 2079-9292 |
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| Abstract | In order to improve the welding efficiency of the ship welding robot, the path planning of the welding robot based on immune optimization is proposed by taking the welding path length and energy loss as the optimization goals. First, on the basis of the definition of the path planning of the welding robot, the grid modeling of the robot’s working environment and the triangular modeling of the welding weldments are carried out. Then, according to the working process of the welding robot, the length objective function, including the welded seam path and the welding torch path without welding, is constructed, and the energy loss function is constructed based on the kinematics and Lagrange function. Finally, the immune optimization algorithm based on cluster analysis and self-circulation is introduced to realize the multi-objective optimization of the path planning for the ship welding robot. The test results of four kinds of ship welding weldments show that compared with the simple genetic algorithm, immune genetic algorithm, ant colony algorithm, artificial bee colony, particle swarm optimization, and immune cloning optimization, the proposed multi-objective immune planning algorithm is the best in terms of planning path length, energy consumption, and stability. Furthermore, the average shortest path and its standard deviation, the average minimum energy consumption and its standard deviation, and the average lowest convergence generation and its standard deviation are reduced by an average of 9.03%, 54.04%, 8.23%, 19.10%, 27.84%, and 52.25%, respectively, which fully verifies the effectiveness and superiority of the proposed welding robot path planning algorithm. |
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| AbstractList | In order to improve the welding efficiency of the ship welding robot, the path planning of the welding robot based on immune optimization is proposed by taking the welding path length and energy loss as the optimization goals. First, on the basis of the definition of the path planning of the welding robot, the grid modeling of the robot’s working environment and the triangular modeling of the welding weldments are carried out. Then, according to the working process of the welding robot, the length objective function, including the welded seam path and the welding torch path without welding, is constructed, and the energy loss function is constructed based on the kinematics and Lagrange function. Finally, the immune optimization algorithm based on cluster analysis and self-circulation is introduced to realize the multi-objective optimization of the path planning for the ship welding robot. The test results of four kinds of ship welding weldments show that compared with the simple genetic algorithm, immune genetic algorithm, ant colony algorithm, artificial bee colony, particle swarm optimization, and immune cloning optimization, the proposed multi-objective immune planning algorithm is the best in terms of planning path length, energy consumption, and stability. Furthermore, the average shortest path and its standard deviation, the average minimum energy consumption and its standard deviation, and the average lowest convergence generation and its standard deviation are reduced by an average of 9.03%, 54.04%, 8.23%, 19.10%, 27.84%, and 52.25%, respectively, which fully verifies the effectiveness and superiority of the proposed welding robot path planning algorithm. |
| Audience | Academic |
| Author | Yuan, Mingxin Gao, Yunqiang Sun, Hongwei Guo, Zhenjie Shen, Yi |
| Author_xml | – sequence: 1 givenname: Yi surname: Shen fullname: Shen, Yi – sequence: 2 givenname: Yunqiang surname: Gao fullname: Gao, Yunqiang – sequence: 3 givenname: Mingxin surname: Yuan fullname: Yuan, Mingxin – sequence: 4 givenname: Hongwei surname: Sun fullname: Sun, Hongwei – sequence: 5 givenname: Zhenjie surname: Guo fullname: Guo, Zhenjie |
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| SubjectTerms | Algorithms Ant colony optimization Cloning Cluster analysis Efficiency Energy consumption Environment models Genetic algorithms Kinematics Mathematical models Mathematical optimization Multiple objective analysis Optimization algorithms Particle swarm optimization Robot dynamics Robots Shipbuilding Shortest-path problems Simulation Standard deviation Technology application Traveling salesman problem Welding Weldments Working conditions |
| Title | Multi-Objective Immune Optimization of Path Planning for Ship Welding Robot |
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