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 (Jixie chuandong)
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.