双臂采茶机器人的协同采摘规划

贾江鸣; 王翔; 周宇杰; 武传宇; 陈建能; 俞蓉; 李昱洁

doi:10.13305/j.cnki.jts.20250617.001

茶叶科学 >

2025 , Vol. 45 >Issue 4: 671 - 686

DOI: https://doi.org/10.13305/j.cnki.jts.20250617.001

研究报告

双臂采茶机器人的协同采摘规划

贾江鸣 ,
王翔 ,
周宇杰 ,
武传宇 ,
陈建能 ,
俞蓉 ,
李昱洁

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1.浙江理工大学机械工程学院,浙江杭州 310018;
2.浙江海洋大学,浙江舟山 316022;
3.浙江农业智能感知与机器人全省重点实验室,浙江杭州 310018

贾江鸣,男,副教授,主要从事智能农业装备及农业机器人方面的研究,Jarky@zstu.edu.cn。

收稿日期: 2024-11-26

修回日期: 2025-01-02

网络出版日期: 2025-08-15

基金资助

国家自然科学基金（U23A20175、52305289）、浙江省领雁研发攻关计划（2022C02052）、国家现代农业产业技术体系（CARS-19）

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Collaborative Picking Planning for A Dual-Arm Tea-Picking Robot

JIA Jiangming ,
WANG Xiang ,
ZHOU Yujie ,
WU Chuanyu ,
CHEN Jianneng ,
YU Rong ,
LI Yujie

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1. School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China;
2. Zhejiang Ocean University, Zhoushan 316022, China;
3. Key Laboratory of Agricultural Intelligent Perception and Robotics of Zhejiang Province, Hangzhou 310018, China

Received date: 2024-11-26

Revised date: 2025-01-02

Online published: 2025-08-15

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摘要

为应对名优茶产业中劳动力短缺、人工成本上升以及采摘精度要求高等问题,多臂采茶机器人成为了近年来的研究热点。提出了一种动态划分作业空间的采摘点分配方法,结合蚁群算法和采摘点优先级综合优化了机械臂的路径规划,以提高采茶机器人的作业效率。仿真结果表明,该方法实现了单芽采摘平均时间为1.41 s,双臂同步作业时间比为91.95%;相比空间二分法的62.86%覆盖率,该方法实现了作业空间的全覆盖。为解决现有深度相机独立作业模式限制,进一步提出了动态新增采摘点规划方法,实现了深度相机与机械臂的同步作业。田间试验结果表明,采茶机器人采用动态划分作业空间的采摘点分配方法与动态新增采摘点规划的双臂协同规划方法后,单芽采摘平均时间为1.52 s,整体效率相较于单臂采茶机器人提高了29.95%。该方法不仅提升了采茶机器人的作业效率,还实现了作业空间的全覆盖,确保了高效协同采摘的实现。

关键词： 采摘机器人; 动态新增采摘点规划; 双机械臂; 协同采摘规划

本文引用格式

贾江鸣 , 王翔 , 周宇杰 , 武传宇 , 陈建能 , 俞蓉 , 李昱洁 . 双臂采茶机器人的协同采摘规划[J]. 茶叶科学, 2025 , 45(4) : 671 -686 . DOI: 10.13305/j.cnki.jts.20250617.001

Abstract

In recent years, multi-arm tea-picking robots have become a research hotspot due to the shortage of labor, rising labor costs, and the demand for high-precision picking in the high-quality tea industry. A collaborative planning method that dynamically allocates the space for picking points was proposed, and the path planning of the robotic arm was optimized by combining the ant colony algorithm and the picking point priority in order to improve the operational efficiency of the tea-picking robot. Simulation results show that the average time for one-shoot picking was 1.41 s, and the time ratio for dual-arm synchronous operation was 91.95%. Compared to the 62.86% coverage rate of the two-space segmentation method, this method achieved full coverage of the space. To overcome the limitations of the existing independent operation mode of the depth camera, a dynamic addition of picking point planning was further proposed, which realized the synchronous operation of the depth camera and the robotic arm. Field experiment results show that the tea-picking robot adopts the picking point allocation method that dynamically divides the operating space and the double-arm collaborative planning method that dynamically divides the space for picking point allocation. The average time for one-shoot picking was 1.52 s, a 29.95% improvement compared to the one-arm tea-picking robot. This method not only significantly improves the operational efficiency of the tea-picking robot but also achieves full coverage of the space, ensuring efficient collaborative picking.

Key words： collaborative picking planning; dynamic picking point addition planning; multi-arm; picking robot

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