基于时间与急动度最优的并联式采茶机器人轨迹规划混合策略

doi:10.3901/JME.2022.09.062

机械工程学报 ›› 2022, Vol. 58 ›› Issue (9): 62-70.doi: 10.3901/JME.2022.09.062

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基于时间与急动度最优的并联式采茶机器人轨迹规划混合策略

杨化林, 钟岩, 姜沅政, 邓芳, 陈龙

青岛科技大学机电工程学院青岛 266061

收稿日期:2021-05-17 修回日期:2021-10-08 出版日期:2022-05-05 发布日期:2022-06-23
通讯作者: 邓芳(通信作者),女,1981年出生,博士,副教授,硕士研究生导师。主要研究方向为数字化设计、船舶运动控制和轨迹规划。E-mail：dengfhelen@163.com E-mail:dengfhelen@163.com
作者简介:杨化林,男,1975年出生,博士,教授,硕士研究生导师。主要研究方向为数字化设计、知识工程、智能农业设备和数字孪生。E-mail：younghualin@163.com
基金资助:
山东省自然科学基金(ZR2019MEE102)和山东省重点研发计划(2018GNC112007)资助项目

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

YANG Hualin, ZHONG Yan, JIANG Yuanzheng, DENG Fang, CHEN Long

College of Mechanical and Electrical Engineering, Qingdao University of Science and Technology, Qingdao 266061

Received:2021-05-17 Revised:2021-10-08 Online:2022-05-05 Published:2022-06-23

摘要/Abstract

摘要： 提出一种基于时间与急动度最优的速度曲线模型方法。分析了当前名优茶的叶芽采摘工作背景,提出一种Delta并联机构与视觉识别技术相结合的名优茶采摘机器人。建立名优茶的采摘轨迹周期并应用了改进的速度曲线模型,采用了Lamé曲线优化采摘轨迹改善Delta机构工作过程中存在的由于竖直水平运动切换引起的加速度突变问题。对调和急动模型完成适应性改进,应用适用于采茶特殊性的粒子群优化算法求解模型中最优的时间间隔参数,从而优化采茶轨迹周期中的工作时间。该模型遵守运动学约束,对采摘轨迹的时间与急动度综合优化,保持良好的轨迹平滑性。实验结果表明,该方法能够缩短采摘时间,提高效率,在急动度抑制方面有更好的性能,为名优茶采摘机器人路径规划提供了一种有效的方式。

关键词: 采茶机器人, 轨迹规划, 急动度, 改进调和急动模型, 粒子群优化

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

中图分类号:

TP242
TP299

杨化林, 钟岩, 姜沅政, 邓芳, 陈龙. 基于时间与急动度最优的并联式采茶机器人轨迹规划混合策略[J]. 机械工程学报, 2022, 58(9): 62-70.

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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基于时间与急动度最优的并联式采茶机器人轨迹规划混合策略

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

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