Hybrid Strategy of Parallel Tea Picking Robot Trajectory Planning Based on Optimal Time and Jerk

doi:10.3901/JME.2022.09.062

Abstract

Abstract: A speed curve model method based on the optimal time and jerk is proposed. The background of the current leaf bud picking of famous tea is analyzed, and a famous tea picking robot combining Delta parallel mechanism and visual recognition technology is proposed. The picking trajectory cycle of famous teas was established and the improved speed curve model is applied, and the Lamé curve was used to optimize the picking trajectory to improve the sudden change of acceleration caused by the switching of vertical and horizontal motion in the working process of the Delta mechanism. The adaptive improvement of the harmonic jerk model is completed, and the particle swarm optimization algorithm suitable for the particularity of tea picking is applied to solve the optimal time interval parameters in the model, thereby optimizing the working time in the tea picking trajectory cycle. The model complies with kinematic constraints, comprehensively optimizes the time and jerk of the picking trajectory, thus can maintain a good trajectory smoothness. Experimental results show that the method can shorten the picking time, improve the efficiency, perform better in jerk suppression, and provide an effective way for path planning of famous tea picking robots.

Key words: tea-plucking robot, trajectory optimization, jerk, improved harmonic jerk model, particle swarm optimization

CLC Number:

TP242
TP299

YANG Hualin, ZHONG Yan, JIANG Yuanzheng, DENG Fang, CHEN Long. Hybrid Strategy of Parallel Tea Picking Robot Trajectory Planning Based on Optimal Time and Jerk[J]. Journal of Mechanical Engineering, 2022, 58(9): 62-70.

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