Trajectory Planning of Camellia Oleifera Pollen Picking Manipulators Based on an Improved Particle Swarm Optimization Algorithm

Li Jun; Zhao Qing; Li Lijun; Wu Zechao; Guo Xin; Fan Ziyan; Gong Hongbin

doi:10.16578/j.issn.1004.2539.2023.02.011

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Trajectory Planning of Camellia Oleifera Pollen Picking Manipulators Based on an Improved Particle Swarm Optimization Algorithm

Design· Calculation | 更新时间：2023-02-25

- Trajectory Planning of Camellia Oleifera Pollen Picking Manipulators Based on an Improved Particle Swarm Optimization Algorithm
- Journal of Mechanical Transmission Vol. 47, Issue 2, Pages: 86-92(2023)
- 作者机构：
  
  中南林业科技大学机电工程学院，湖南长沙 410004
- 作者简介：
- 基金信息：
- DOI：10.16578/j.issn.1004.2539.2023.02.011
  CLC：
- Published：15 February 2023，
  
  Received：08 January 2022，
  
  Revised：29 January 2022，
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李骏,赵青,李立君等.基于改进粒子群算法的油茶花粉采摘机械臂轨迹规划[J].机械传动,2023,47(02):86-92.

Li Jun,Zhao Qing,Li Lijun,et al.Trajectory Planning of Camellia Oleifera Pollen Picking Manipulators Based on an Improved Particle Swarm Optimization Algorithm[J].Journal of Mechanical Transmission,2023,47(02):86-92.
李骏,赵青,李立君等.基于改进粒子群算法的油茶花粉采摘机械臂轨迹规划[J].机械传动,2023,47(02):86-92. DOI： 10.16578/j.issn.1004.2539.2023.02.011.

Li Jun,Zhao Qing,Li Lijun,et al.Trajectory Planning of Camellia Oleifera Pollen Picking Manipulators Based on an Improved Particle Swarm Optimization Algorithm[J].Journal of Mechanical Transmission,2023,47(02):86-92. DOI： 10.16578/j.issn.1004.2539.2023.02.011.

摘要

针对人工收集油茶花粉存在劳动强度大、效率低等问题，基于油茶花的生长特性，设计了一种油茶花粉采摘机器人。以油茶花粉采摘机械臂为研究对象，采用D-H方法对其进行建模和正、逆运动学分析；在Matlab软件环境下，采用蒙特卡罗方法求解末端手爪的工作空间，得到机械臂末端工作空间的点云图像。仿真数据表明，所设计的机械臂能够很好地满足油茶花粉采摘要求。由于传统机器人轨迹规划存在效率低、运行不稳定等问题，提出了一种改进粒子群（IPSO）算法对油茶花粉采摘机械臂的轨迹进行优化。该方法以时间为适应度函数，有效地将5-5-5多项式插值函数与IPSO算法相结合。通过对比传统遗传算法（SGA）与传统粒子群算法（SPSO），表明IPSO算法能更好地适用于油茶花粉采摘机械臂的时间最优轨迹规划。

Abstract

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.

关键词

油茶花粉采摘机器人D-H法粒子群算法5-5-5多项式轨迹规划

Keywords

Camellia oleifera pollen picking robotD-H methodParticle swarm optimization algorithm5-5-5 polynomialTrajectory planning

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