Trajectory Planning of Camellia Oleifera Pollen Picking Manipulators Based on an Improved Particle Swarm Optimization Algorithm
Aiming at the problems of high labor intensity and low efficiency in manually collecting camellia pollen, a camellia pollen picking robot is designed based on the growth characteristics of camellia flower. Taking the camellia oleifera pollen picking manipulator as the research object, the D-H method...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Transmission
2023-02-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2023.02.011 |
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| author | Li Jun Zhao Qing Li Lijun Wu Zechao Guo Xin Fan Ziyan Gong Hongbin |
| author_facet | Li Jun Zhao Qing Li Lijun Wu Zechao Guo Xin Fan Ziyan Gong Hongbin |
| author_sort | Li Jun |
| collection | DOAJ |
| description | Aiming at the problems of high labor intensity and low efficiency in manually collecting camellia pollen, a camellia pollen picking robot is designed based on the growth characteristics of camellia flower. Taking the camellia oleifera pollen picking manipulator as the research object, the D-H method is used to model and analyze its forward and inverse kinematics. In the Matlab software environment, the Monte Carlo method is used to solve the workspace of the end claw, and the point cloud image of the manipulator end workspace is obtained. The simulation data shows that the designed manipulator can well meet the requirements of camellia oleifera pollen picking. Due to the low efficiency and unstable operation of traditional robot trajectory planning, an improved particle swarm optimization (IPSO) algorithm is proposed to optimize the trajectory of camellia pollen picking manipulator. This method takes time as the fitness function and effectively combines 5-5-5 polynomial interpolation function with IPSO algorithm. The comparison between traditional genetic algorithm (SGA) and traditional particle swarm optimization (SPSO) shows that the IPSO algorithm can be better applied to the time optimal trajectory planning of camellia oleifera pollen picking manipulators. |
| format | Article |
| id | doaj-art-d22ed8ab33aa477c9ba1ff3851521468 |
| institution | Kabale University |
| issn | 1004-2539 |
| language | zho |
| publishDate | 2023-02-01 |
| publisher | Editorial Office of Journal of Mechanical Transmission |
| record_format | Article |
| series | Jixie chuandong |
| spelling | doaj-art-d22ed8ab33aa477c9ba1ff38515214682025-01-10T14:56:58ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392023-02-0147869234891720Trajectory Planning of Camellia Oleifera Pollen Picking Manipulators Based on an Improved Particle Swarm Optimization AlgorithmLi JunZhao QingLi LijunWu ZechaoGuo XinFan ZiyanGong HongbinAiming at the problems of high labor intensity and low efficiency in manually collecting camellia pollen, a camellia pollen picking robot is designed based on the growth characteristics of camellia flower. Taking the camellia oleifera pollen picking manipulator as the research object, the D-H method is used to model and analyze its forward and inverse kinematics. In the Matlab software environment, the Monte Carlo method is used to solve the workspace of the end claw, and the point cloud image of the manipulator end workspace is obtained. The simulation data shows that the designed manipulator can well meet the requirements of camellia oleifera pollen picking. Due to the low efficiency and unstable operation of traditional robot trajectory planning, an improved particle swarm optimization (IPSO) algorithm is proposed to optimize the trajectory of camellia pollen picking manipulator. This method takes time as the fitness function and effectively combines 5-5-5 polynomial interpolation function with IPSO algorithm. The comparison between traditional genetic algorithm (SGA) and traditional particle swarm optimization (SPSO) shows that the IPSO algorithm can be better applied to the time optimal trajectory planning of camellia oleifera pollen picking manipulators.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2023.02.011Camellia oleifera pollen picking robotD-H methodParticle swarm optimization algorithm5-5-5 polynomialTrajectory planning |
| spellingShingle | Li Jun Zhao Qing Li Lijun Wu Zechao Guo Xin Fan Ziyan Gong Hongbin Trajectory Planning of Camellia Oleifera Pollen Picking Manipulators Based on an Improved Particle Swarm Optimization Algorithm Jixie chuandong Camellia oleifera pollen picking robot D-H method Particle swarm optimization algorithm 5-5-5 polynomial Trajectory planning |
| title | Trajectory Planning of Camellia Oleifera Pollen Picking Manipulators Based on an Improved Particle Swarm Optimization Algorithm |
| title_full | Trajectory Planning of Camellia Oleifera Pollen Picking Manipulators Based on an Improved Particle Swarm Optimization Algorithm |
| title_fullStr | Trajectory Planning of Camellia Oleifera Pollen Picking Manipulators Based on an Improved Particle Swarm Optimization Algorithm |
| title_full_unstemmed | Trajectory Planning of Camellia Oleifera Pollen Picking Manipulators Based on an Improved Particle Swarm Optimization Algorithm |
| title_short | Trajectory Planning of Camellia Oleifera Pollen Picking Manipulators Based on an Improved Particle Swarm Optimization Algorithm |
| title_sort | trajectory planning of camellia oleifera pollen picking manipulators based on an improved particle swarm optimization algorithm |
| topic | Camellia oleifera pollen picking robot D-H method Particle swarm optimization algorithm 5-5-5 polynomial Trajectory planning |
| url | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2023.02.011 |
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