果蔬采摘机器手系统设计与控制技术研究现状和发展趋势

doi:10.12133/j.smartag.2020.2.4.202011-SA004

摘要/Abstract

摘要：

鲜食果蔬收获是难以实现机械化作业的生产环节，高效低损采摘也是农业机器人研发领域中的难题，导致目前市场化的自动化果蔬采摘装备生产应用几乎空白。针对鲜食果蔬采摘需求，为改善人工采摘费时费力、效率低下、自动化程度低的问题，近30年来，国内外学者设计了一系列自动化采摘设备，推动了农业机器人技术的发展。在研发鲜食果蔬采摘设备时，首先要确定采收对象和采收场景，针对作物的生长位置、形状和重量、场景的复杂程度、所需自动化程度，通过复杂度预估、力学特性分析、姿态建模等方式，明确农业机器人的设计需求。其次，作为整个采摘动作的核心执行者，采摘机器人的末端执行器设计尤为重要。本文对采摘机器人末端执行器的结构进行了分类，总结了末端执行器的设计流程与方法，阐述了常见的末端执行器驱动方式、切割方案，并对果实收集机构进行了概括。再次，本文概述了采摘机器人的总体控制方案、识别定位方法、避障方法及自适应控制方案、品质分类方法以及人机交互、多机协作方案。为了总体评价采摘机器人的性能，本文还提出了平均采摘效率、长期采摘效率、采收质量、损伤率和漏采率指标。最后，本文对自动化采摘机械的总体发展趋势进行了展望，指明了采摘机器手系统将向着采摘目标场景通用化、结构形式多样化、全自动化、智能化、集群化方向发展的趋势。

关键词: 采摘机械, 场景分析, 机械抓手, 自动控制, 评价指标, 发展趋势

Abstract:

Vegetable and fruit harvesting is the most difficult production process to achieve mechanized operations. High-efficiency and low-loss picking is also a worldwide problem in the field of agricultural robot research and development, resulting in few production and application equipment currently on the market. In response to the demand for picking vegetables and fruits, to improve the time-consuming, labor-intensive, low-efficiency, and low-automation problems of manual picking, scholars have designed a series of automated picking equipment in the recent 30 years, which has promoted the development of agricultural robot technology. In the research and development of fresh vegetable and fruit picking equipment, firstly, the harvesting object and harvesting scene should be determined according to the growth position, shape and weight of the crop, the complexity of the scene, the degree of automation required, through complexity estimation, mechanical characteristics analysis, pose modeling and other methods clarify the design requirements of agricultural robots. Secondly, as the core executor of the entire picking action, the design of the end effector of the picking robot is particularly important. In this article, the structure of the end effector was classified, the design process and method of the end effectors were summarized, the common end effector driving methods and cutting methods were expounded, and the fruit collection mechanism was summarized. Furthermore, the overall control scheme of the picking robot, recognition and positioning method, adaptive control scheme of obstacle avoidance method, quality classification method, human-computer interaction and multi-machine cooperation scheme were summarized. Finally, in order to evaluate the performance of the picking robot overall, the indicators of average picking efficiency, long-term picking efficiency, harvest quality, picking maturity rate and missed picking rate were proposed. The overall development trend was pointed that picking robots would develop toward generalization of picking target scenes, diversified structures, full automation, intelligence, and clustering were put forward in the end.

Key words: picking machinery, scene analysis, mechanical gripper, automatic control, evaluation index, development trend

中图分类号:

TP241.3

吴剑桥, 范圣哲, 贡亮, 苑进, 周强, 刘成良. 果蔬采摘机器手系统设计与控制技术研究现状和发展趋势[J]. 智慧农业（中英文）, 2020, 2(4): 17-40.

WU Jianqiao, FAN Shengzhe, GONG Liang, YUAN Jin, ZHOU Qiang, LIU Chengliang. Research Status and Development Direction of Design and Control Technology of Fruit and Vegetable Picking Robot System[J]. Smart Agriculture, 2020, 2(4): 17-40.

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