Trajectory Planning Application of Rehabilitation Robots Based on Improved CSA Algorithm
With the aging global population, there are more patients with hemiplegia caused by stroke. The demand for rehabilitation robots to assist rehabilitation therapists is also increasing. To solve the above problems, a reasonable trajectory planning of the rehabilitation robot joints is constructed to...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10363181/ |
| _version_ | 1797374432367345664 |
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| author | Lizhen Xia |
| author_facet | Lizhen Xia |
| author_sort | Lizhen Xia |
| collection | DOAJ |
| description | With the aging global population, there are more patients with hemiplegia caused by stroke. The demand for rehabilitation robots to assist rehabilitation therapists is also increasing. To solve the above problems, a reasonable trajectory planning of the rehabilitation robot joints is constructed to achieve rehabilitation assistance, improve safety and practicality.Firstly, a Kinematics model is constructed, and B-spline is applied to realize the trajectory planning of the rehabilitation robot. By introducing crow search algorithm and multiple crow search algorithms, the energy impact multi-objective optimization for the upper limb movement of the rehabilitation robot is carried out. Relevant experiments are designed to compare and verify the optimization effects of the algorithms. From the results, by optimizing the crow search algorithm, only 25.36% and 34.20% of the impact and energy are used. The average impact size per unit of time decreases by 74.68%. The energy consumption per unit time decreases by 65.39%.After optimizing the crow search algorithm, the impact and energy per unit time are only 14.41% and 17.25%, respectively. The energy per unit time decreases by 74.53%, and the impact decreases by 82.97%. Compared with other algorithms, the space complexity of the improved method is very small, and the standard deviation is 0.03. The optimization algorithm performs well in trajectory planning optimization. It is of great significance in the trajectory planning and rehabilitation role of rehabilitation robots. |
| first_indexed | 2024-03-08T19:04:44Z |
| format | Article |
| id | doaj.art-663ac41d89314bc58135c3b750f6e66d |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-08T19:04:44Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-663ac41d89314bc58135c3b750f6e66d2023-12-28T00:03:46ZengIEEEIEEE Access2169-35362023-01-011114461714463010.1109/ACCESS.2023.334373410363181Trajectory Planning Application of Rehabilitation Robots Based on Improved CSA AlgorithmLizhen Xia0https://orcid.org/0009-0002-9977-5705Department of Information Engineering, Henan Technical Institute, Zhengzhou, ChinaWith the aging global population, there are more patients with hemiplegia caused by stroke. The demand for rehabilitation robots to assist rehabilitation therapists is also increasing. To solve the above problems, a reasonable trajectory planning of the rehabilitation robot joints is constructed to achieve rehabilitation assistance, improve safety and practicality.Firstly, a Kinematics model is constructed, and B-spline is applied to realize the trajectory planning of the rehabilitation robot. By introducing crow search algorithm and multiple crow search algorithms, the energy impact multi-objective optimization for the upper limb movement of the rehabilitation robot is carried out. Relevant experiments are designed to compare and verify the optimization effects of the algorithms. From the results, by optimizing the crow search algorithm, only 25.36% and 34.20% of the impact and energy are used. The average impact size per unit of time decreases by 74.68%. The energy consumption per unit time decreases by 65.39%.After optimizing the crow search algorithm, the impact and energy per unit time are only 14.41% and 17.25%, respectively. The energy per unit time decreases by 74.53%, and the impact decreases by 82.97%. Compared with other algorithms, the space complexity of the improved method is very small, and the standard deviation is 0.03. The optimization algorithm performs well in trajectory planning optimization. It is of great significance in the trajectory planning and rehabilitation role of rehabilitation robots.https://ieeexplore.ieee.org/document/10363181/Trajectory planningcrow search algorithmrehabilitation robotsmulti objective optimizationmultiple group methods |
| spellingShingle | Lizhen Xia Trajectory Planning Application of Rehabilitation Robots Based on Improved CSA Algorithm IEEE Access Trajectory planning crow search algorithm rehabilitation robots multi objective optimization multiple group methods |
| title | Trajectory Planning Application of Rehabilitation Robots Based on Improved CSA Algorithm |
| title_full | Trajectory Planning Application of Rehabilitation Robots Based on Improved CSA Algorithm |
| title_fullStr | Trajectory Planning Application of Rehabilitation Robots Based on Improved CSA Algorithm |
| title_full_unstemmed | Trajectory Planning Application of Rehabilitation Robots Based on Improved CSA Algorithm |
| title_short | Trajectory Planning Application of Rehabilitation Robots Based on Improved CSA Algorithm |
| title_sort | trajectory planning application of rehabilitation robots based on improved csa algorithm |
| topic | Trajectory planning crow search algorithm rehabilitation robots multi objective optimization multiple group methods |
| url | https://ieeexplore.ieee.org/document/10363181/ |
| work_keys_str_mv | AT lizhenxia trajectoryplanningapplicationofrehabilitationrobotsbasedonimprovedcsaalgorithm |