A new modified grey wolf optimization algorithm proposal for a fundamental engineering problem in robotics
In this study, the solution of inverse kinematics, which is the most fundamental problem in the field of robotics, is handled with the grey wolf optimization algorithm. Grey wolves belong to the Canis Lupus species and they act in a number of organization and cooperation while hunting in swarm in na...
| Published in: | Neural Computing and Applications |
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| Main Author: | |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Springer London Ltd
2021
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| Subjects: | |
| Online Access: | https://hdl.handle.net/20.500.14002/34 https://doi.org/10.1007/s00521-021-06050-2 |
| Summary: | In this study, the solution of inverse kinematics, which is the most fundamental problem in the field of robotics, is handled with the grey wolf optimization algorithm. Grey wolves belong to the Canis Lupus species and they act in a number of organization and cooperation while hunting in swarm in nature. Thanks to this heuristic technique, which was created by transferring this collaboration first to the algorithm and then to the code, many engineering problems were quickly solved. Similarly, in this study, inverse kinematics solution, which is an engineering problem, was solved with the grey wolf swarm optimization technique. The results are given in comparison with the traditional grey wolf algorithm and the modified grey wolf algorithm obtained by improving one of the control parameters of this algorithm and with other swarm-based algorithms. According to these results, it has been clearly observed that the grey wolf algorithm produces similar results with other swarm-based algorithms, but the modified grey wolf algorithm produces better values. This shows that the grey wolf optimization algorithm can achieve much better convergence by modifying or strengthening it. |
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