水果采摘机械臂运动规划研究进展与发展趋势水果采摘机械臂运动规划研究进展与发展趋势

doi:10.12398/j.issn.2096-7217.2021.02.002

摘要/Abstract

摘要： 针对水果采摘的现存问题，对水果采摘机械臂进行合理的运动规划，以达到解放人力、提高采摘效率、降低采收成本的目的。分析水果采摘机器人的国内外研究进展，并就其机械臂采摘过程的关键算法进行比较，最后针对机械臂轨迹规划平滑性差、效率低提出采用B样条曲线和生物智能的算法；针对搜索效率低和局部最小值的问题提出采用基于图搜索的改进算法、改进人工势场法和深度强化学习算法等对策，并在新的运动规划算法、机械臂硬件以及底层控制和多机械臂协作控制等方面进行展望。

关键词: 水果采摘, 智能化, 非结构性环境, 机械臂, 运动规划

Abstract: Aiming to solve the existing problems of fruit picking, proper movement planning of fruit picking mechanical arm is carried out to improve the efficiency of fruit picking, liberate manpower, and reduce the harvest cost. This paper analyzes the research status of fruitpicking robots at home and abroad and compares the key algorithms of the picking process of the robot arm. Finally, aiming to solve the poor smoothness and low efficiency of the trajectory planning of the robot arm, the algorithm using the Bspline curve and biological intelligence is proposed. In order to solve the problems of low search efficiency and local minimum, the improved algorithm based on graph search, the improved artificial potential field method, and the deep reinforcement learning algorithm are proposed, and the new motion planning algorithm, manipulator hardware, lowlevel control, and multimanipulator cooperative control are prospected.

Key words: fruit picking, intelligent, unstructured environment, robot arm, motion planning

中图分类号:

S225.93

段洁利, 王昭锐, 叶磊, 杨洲, . 水果采摘机械臂运动规划研究进展与发展趋势水果采摘机械臂运动规划研究进展与发展趋势[J]. 智能化农业装备学报（中英文）, 2021, 2(2): 7-17.

Jieli Duan, , Zhaorui Wang, Lei Ye, Zhou Yang, , . Research progress and development trend of #br# motion planning of fruit picking robot arm#br#[J]. Journal of Intelligent Agricultural Mechanization (in Chinese and English), 2021, 2(2): 7-17.

参考文献

［1］王喜文. 工业4.0带来机器人的进化［J］. 物联网技术, 2015, 5(10): 2.
［2］王新. 基于球形腕的灵巧机器人零力控制研究［D］. 大连: 大连理工大学, 2016.
［3］王田苗, 陶永. 我国工业机器人技术现状与产业化发展战略［J］. 机械工程学报, 2014, 50(9): 1-13.
Wang Tianmiao, Tao Yong. Research status and industrialization development strategy of Chinese industrial robot ［J］. Journal of Mechanical Engineering, 2014, 50(9): 1-13.
［4］宋健, 张铁中, 徐丽明, 等. 果蔬采摘机器人研究进展与展望［J］. 农业机械学报, 2006, 37(5): 158-162.
Song Jian, Zhang Tiezhong, Xu Liming,et al. Research actuality and prospect of picking robot for fruits and vegetables ［J］. Transactions of the Chinese Society for Agricultural Machinery, 2006, 37(5): 158-162.
［5］李国利, 姬长英, 翟力欣. 果蔬采摘机器人末端执行器研究进展与分析［J］. 中国农机化学报, 2014, 35(5): 231-236, 240.
Li Guoli, Ji Changying, Zhai Lixin. Research progress and analysis of endeffector for fruits and vegetables picking robot ［J］. Journal of Chinese Agricultural Mechanization, 2014, 35(5): 231-236, 240.
［6］李会宾, 史云. 果园采摘机器人研究综述［J］. 中国农业信息, 2019, 31(6): 1-9.
Li Huibin, Shi Yun. Review on orchard harvesting robots ［J］. China Agricultural Informatics, 2019, 31(6): 1-9.
［7］王海楠, 弋景刚, 张秀花. 番茄采摘机器人识别与定位技术研究进展［J］. 中国农机化学报, 2020, 41(5): 188-196.
Wang Hainan, Yi Jinggang, Zhang Xiuhua. Research progress on recognition and localization technology of tomato picking robot ［J］. Journal of Chinese Agricultural Mechanization, 2020, 41(5): 188-196.
［8］杨保海, 任全会, 李海生. 复杂环境下果园机器人路径规划方法研究［J］. 中国农机化学报, 2021, 42(2): 134-138.
Yang Baohai, Ren Quanhui, Li Haisheng. Research on path planning method of orchard robot in complex environment ［J］. Journal of Chinese Agricultural Mechanization, 2021, 42(2): 134-138.
［9］计时鸣, 黄希欢. 工业机器人技术的发展与应用综述［J］. 机电工程, 2015, 32(1): 1-13.
Ji Shimin, Huang Xihuan. Review of development and application of industrial robot technology ［J］. Mechanical & Electrical Engineering Magazine, 2015, 32(1): 1-13.
［10］李攀. 苹果采摘机器人目标识别及轨迹规划［D］. 西安: 西安理工大学, 2019.
［11］张哲. 柑橘采摘机器人采摘姿态及序列研究［D］. 重庆: 重庆理工大学, 2018.
［12］李志鹏. 脐橙采摘机械手的设计与研究［D］. 南昌: 南昌大学, 2020.
［13］ Luke D. Panasonic built a robot gentle enough to pick tomatoes, but not exactly graceful ［EB/OL］. http://www.digitaltrends.com/cooltech/tomatoespickerrobot/, 2018-01-02.
［14］王丽丽. 番茄采摘机器人关键技术研究［D］. 北京: 北京工业大学, 2017.
［15］李占坤. 果树采摘机器人控制系统研究与设计［D］. 镇江: 江苏大学, 2010.
［16］顾宝兴. 智能移动式水果采摘机器人系统的研究［D］. 南京: 南京农业大学, 2012.
［17］熊俊涛, 叶敏, 邹湘军, 等. 多类型水果采摘机器人系统设计与性能分析［J］. 农业机械学报, 2013, 44(S1): 230-235.
Xiong Juntao, Ye Min, Zou Xiangjun,et al. System design and performance analysis on multitype fruit harvesting robot ［J］. Transactions of the Chinese Society for Agricultural Machinery, 2013, 44(S1): 230-235.
［18］胡友呈. 自然环境下柑橘采摘机器人的目标识别与定位方法研究［D］. 重庆: 重庆理工大学, 2018.
［19］ Gasparetto A, Boscariol P, Lanzutti A, et al. Path planning and trajectory planning algorithms: A general overview ［M］. Springer International Publishing, 2015.
［20］郭勇, 赖广. 工业机器人关节空间轨迹规划及优化研究综述［J］. 机械传动, 2020, 44(2): 154-165.
Guo Yong, Lai Guang. Review of joint space trajectory planning and optimization for industrial robot ［J］. Journal of Mechanical Transmission, 2020, 44(2): 154-165.
［21］李扬, 程维明, 宫成文, 等. 5DOF机械臂运动学分析及运动轨迹规划［J］. 中国农机化学报, 2018, 39(9): 16-21.
Li Yang, Cheng Weiming, Gong Chengwen, et al.Kinematics analysis and motion trajectory planning of 5DOF manipulator ［J］. Journal of Chinese Agricultural Mechanization, 2018, 39(9): 16-21.
［22］蔡自兴, 谢斌. 机器人学［M］. 北京: 清华大学出版社, 2015.
［23］占涛, 杨光友. 基于PSO算法的双臂机器人时间最优轨迹规划［J］. 中国农机化学报, 2017, 38(6): 82-88, 108.
Zhan Tao, Yang Guangyou. Timeoptimal trajectory planning of dual arm robot based on PSO algorithm ［J］. Journal of Chinese Agricultural Mechanization, 2017, 38(6): 82-88, 108.
［24］马睿, 胡晓兵, 殷国富, 等. 六关节工业机器人最短时间轨迹优化［J］. 机械设计与制造, 2014(4): 30-32, 35.
Ma Rui, Hu Xiaobing, Yin Guofu,et al. The shortest time optimal planning of 6DOF industrial robots trajectory ［J］. Machinery Design & Manufacture, 2014(4): 30-32, 35.
［25］ Perumalsamy G, Visweswaran P, Jose J, et al. Quintic interpolation joint trajectory for the path planning of a serial twoaxis robotic arm for PFBR steam generator inspection ［M］. Machines, Mechanism and Robotics. Springer, Singapore, 2019: 637-648.
［26］罗欣. 机器人平滑运动轨迹规划及控制方法的研究［D］. 广州: 华南理工大学, 2017.
［27］ Boryga M, Grabos＇ A. Planning of manipulator motion trajectory with higherdegree polynomials use ［J］. Mechanism and Machine Theory, 2009, 44(7): 1400-1419.
［28］李林峰, 马蕾. 三次均匀B样条在工业机器人轨迹规划中的应用研究［J］. 科学技术与工程, 2013, 13(13): 3621-3625, 3646.
Li Linfeng, Ma Lei. A research on the cubic uniform Bspline curve and its application on trajectory planning algorithm of industry robot ［J］. Science Technology and Engineering, 2013, 13(13): 3621-3625, 3646.
［29］王幼民. 机械臂关节空间B样条曲线轨迹规划［J］. 安徽机电学院学报, 2000, 15(2): 21-26.
Wang Youmin. Bsplines path planning for manipulator in joint coordinates ［J］. Journal of Anhui Institute of Mechanical and Electrical Engineering, 2000, 15(2): 21-26.
［30］王卫忠, 赵杰, 高永生, 等. 机器人的平面曲线轨迹规划方法［J］. 哈尔滨工业大学学报, 2008, 40(3): 389-392.
Wang Weizhong, Zhao Jie, Gao Yongsheng,et al. An approach for robot plane curve trajectory planning ［J］. Journal of Harbin Institute of Technology, 2008, 40(3): 389-392.
［31］付荣, 居鹤华. 基于粒子群优化的时间最优机械臂轨迹规划算法［J］. 信息与控制, 2011, 40(6): 802-808.
Fu Rong, Ju Hehua. Timeoptimal trajectory planning algorithm for manipulator based on PSO ［J］. Information and Control, 2011, 40(6): 802-808.
［32］ Clerc M. The swarm and the queen: Towards a deterministic and adaptive particle swarm optimization ［C］. Proceedings of the 1999 Congress on Evolutionary ComputationCEC99 (Cat. No 99TH8406). IEEE, 1999, 3: 1951-1957.
［33］ Chyan G S, Ponnambalam S G. Obstacle avoidance control of redundant robots using variants of particle swarm optimization ［J］. Robotics and ComputerIntegrated Manufacturing, 2012, 28(2): 147-153.
［34］ Lin C J, Li T, Kuo P H, et al. Integrated particle swarm optimization algorithm based obstacle avoidance control design for home service robot ［J］. Computers & Electrical Engineering, 2016, 56: 748-762.
［35］ Yue S, Henrich D, Xu W L, et al. Pointtopoint trajectory planning of flexible redundant robot manipulators using genetic algorithms ［J］. Robotica, 2002, 20(3): 269-280.
［36］ Marcos M G, Machado J A T, AzevedoPerdicoúlis T P. Trajectory planning of redundant manipulators using genetic algorithms ［J］. Communications in Nonlinear Science and Numerical Simulation, 2009, 14(7): 2858-2869.
［37］ AbuDakka F J, Valero F J, Suer J L, et al. A direct approach to solving trajectory planning problems using genetic algorithms with dynamics considerations in complex environments ［J］. Robotica, 2015, 33(3): 669-683.
［38］童亮, 陆际联. 基于强化学习的机器人操作手轨迹规划方法研究［J］. 制造技术与机床, 2005(5): 33-36.
Tong Liang, Lu Jilian. Research on pathplanning of robot manipulator based on reinforcement learning ［J］. Manufacturing Technology & Machine Tool, 2005(5): 33-36.
［39］赵毓, 管公顺, 郭继峰, 等. 基于多智能体强化学习的空间机械臂轨迹规划［J］. 航空学报, 2021, 42(1): 266-276.
Zhao Yu, Guan Gongshun, Guo Jifeng, et al. Trajectory planning of space manipulator based on multiagent reinforcement learning ［J］. Acta Aeronautica et Astronautica Sinica, 2021, 42(1): 266-276.
［40］靳栋银, 李跃, 邵振洲, 等. 面向机械臂轨迹规划的强化学习奖励函数设计［J/OL］. 计算机工程与应用: 1-9［2021-07-08］. http://kns.cnki.net/kcms/detail/11.2127.TP.20210521.1249.018.html.
Jin Dongyin, Li Yue, Shao Zhenzhou,et al. Design of reinforcement learning reward function for trajectory planning of manipulator ［J/OL］. Computer Engineering and Applications: 1-9［2021-07-08］. http://kns.cnki.net/kcms/detail/11.2127.TP.20210521.1249.018.html.
［41］ Wang Huijuan, Yu Yuan, Yuan Quanbo. Application of Dijkstra algorithm in robot pathplanning ［C］. 2011 Second International Conference on Mechanic Automation and Control Engineering. IEEE, 2011.
［42］ Deng Y, Chen Y, Zhang Y, et al. Fuzzy Dijkstra algorithm for shortest path problem under uncertain environment ［J］. Applied Soft Computing, 2012, 12(3): 1231-1237.
［43］ Luo M, Hou X, Yang J. Surface optimal path planning using an extended Dijkstra algorithm ［J］. IEEE Access, 2020, 8: 147827-147838.
［44］赵真明, 孟正大. 基于加权A*算法的服务型机器人路径规划［J］. 华中科技大学学报(自然科学版), 2008(S1): 196-198.
Zhao Zhenming, Meng Zhengda. Path planning of service mobile robot based on addingweight A* algorithm ［J］. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2008(S1): 196-198.
［45］ Henten E J, Hemming J, Tuijl B, et al. An autonomous robot for harvesting cucumbers in greenhouses ［J］. Autonomous Robots, 2002, 13(3): 241-258.
［46］尹建军, 武传宇, Yang Simon X, 等. 番茄采摘机器人机械臂避障路径规划［J］. 农业机械学报, 2012, 43(12): 171-175, 157.
Yin Jianjun, Wu Chuanyu, Yang Simon X, et al. Obstacleavoidance path planning of robot arm for tomatopicking robot ［J］. Transactions of the Chinese Society for Agricultural Engineering, 2012, 43(12): 171-175, 157.
［47］赵金龙, 晁永生, 袁逸萍. 基于A*算法和三次样条的工业机械臂路径平滑性研究［J］. 机械设计与研究, 2019,35(1): 61-64, 69.
Zhao Jinlong, Chao Yongsheng, Yuan Yiping. The research of industrial manipulator path smoothness based on A* algorithm and cubic spline function ［J］. Machine Design Research, 2019, 35(1): 61-64, 69.
［48］沈旭明. 基于时序A*算法的双臂机器人避障路径规划研究［D］. 杭州: 浙江工业大学, 2020.
［49］张许有, 刘有余. 基于位置代价A*算法的机械臂避障路径规划［J］. 机械设计, 2021, 38(2): 108-113.
Zhang Xuyou, Liu Youyu. Path planning of obstacle avoidance for manipulators based on position cost A* algorithm ［J］. Journal of Machine Design, 2021, 38(2):108-113.
［50］ Hargas Y, Mokrane A, Hentout A, et al. Mobile manipulator path planning based on artificial potential field: Application on RobuTER/ULM ［C］. 2015 4th International Conference on Electrical Engineering (ICEE). IEEE, 2015: 1-6.
［51］ Gai S N, Sun R, Chen S J, et al. 6DOF robotic obstacle avoidance path planning based on artificial potential field method ［C］. 2019 16th International Conference on Ubiquitous Robots (UR). IEEE, 2019: 165-168.
［52］王俊龙, 张国良, 羊帆, 等. 改进人工势场法的机械臂避障路径规划［J］. 计算机工程与应用, 2013, 49(21): 266-270.
Wang Junlong, Zhang Guoliang, Yang Fan,et al. Improved artificial field method on obstacle avoidance path planning for manipulator ［J］. Computer Engineering and Applications, 2013, 49(21): 266-270.
［53］汪首坤, 朱磊, 王军政. 基于导航势函数法的六自由度机械臂避障路径规划［J］. 北京理工大学学报, 2015, 35(2): 186-191.
Wang Shoukun, Zhu Lei, Wang Junzheng. Path plan of 6DOF robot manipulators in obstacle environment based on navigation potential function ［J］. Transactions of Beijing Institute of Technology, 2015, 35(2): 186-191.
［54］ Zhang N, Zhang Y, Ma C, et al. Path planning of sixDOF serial robots based on improved artificial potential field method ［C］. 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, 2017: 617-621.
［55］曹博, 毕树生, 郑晶翔, 等. 改进人工势场法的冗余机械臂避障算法［J］. 哈尔滨工业大学学报, 2019, 51(7): 184-191.
Cao Bo, Bi Shusheng, Zheng Jingxiang, et al. Obstacle avoidance algorithm for redundant manipulator of improved artificial potential field method ［J］. Journal of Harbin Institute of Technology, 2019, 51(7): 184-191.
［56］马豪男, 张志安, 黎晴亮. 改进人工势场法的双机械臂路径规划算法［J］. 机械传动, 2021, 45(6): 77-84.
Ma Haonan, Zhang Zhian, Li Qinliang. Improved artificial potential field method for dualmanipulator path planning algorithm ［J］. Journal of Mechanical Transmission, 2021, 45(6): 77-84.
［57］何兆楚, 何元烈, 曾碧. RRT与人工势场法结合的机械臂避障规划［J］. 工业工程, 2017, 20(2): 56-63.
He Zhaochu, He Yuanlie, Zeng Bi. Obstacle avoidence path planning forrobot arm based on mixed algorithm of artificial potential field method and RRT ［J］. Industrial Engineering Journal, 2017, 20(2): 56-63.
［58］祝敬, 杨马英. 基于改进人工势场法的机械臂避障路径规划［J］. 计算机测量与控制, 2018, 26(10): 205-210.
Zhu Jing, Yang Maying. Path planning of manipulator to avoid obstacle based on improved artificial potential field method ［J］. Computer Measurement & Control, 2018, 26(10): 205-210.
［59］孙泾辉, 朱毅, 卢军. 人工势场法与A*算法结合的机械臂避障路径规划研究［J］. 成都信息工程大学学报, 2019, 34(3): 263-266.
Sun Jinghui, Zhu Yi, Lu Jun. Research onobstacle avoidance path planning of manipulator based on artificial potential field method and A* algorithm ［J］. Journal of Chengdu University of Information Technology, 2019, 34(3): 263-266.
［60］ Bohlin R, Kavraki L E. Path planning using lazy PRM ［C］. Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No 00CH37065). IEEE, 2000, 1: 521-528.
［61］ Sánchez G, Latombe J C. On delaying collision checking in PRM planning: Application to multirobot coordination ［J］. The International Journal of Robotics Research, 2002, 21(1): 5-26.
［62］ Masehian E, Sedighizadeh D. A multiobjective PSObased algorithm for robot path planning ［C］. 2010 IEEE International Conference on Industrial Technology. IEEE, 2010: 465-470.
［63］邹宇星, 李立君, 高自成. 基于改进PRM的采摘机器人机械臂避障路径规划［J］. 传感器与微系统, 2019, 38(1): 52-56.
Zou Yuxing, Li Lijun, Gao Zicheng. Obstacle avoidance path planning for harvesting robot arm based on improved PRM ［J］. Transducer and Microsystem Technologies, 2019, 38(1): 52-56.
［64］阳涵疆, 李立君, 高自成. 基于关节构形空间的混联采摘机械臂避障路径规划［J］. 农业工程学报, 2017, 33(4): 55-62.
Yang Hanjiang, Li Lijun, Gao Zicheng. Obstacle avoidance path planning of hybrid harvesting manipulator based on joint configuration space ［J］. Transactions of the Chinese Society of Agricultural Engineering, 2017, 33(4): 55-62.
［65］ Bertram D, Kuffner J, Dillmann R, et al. An integrated approach to inverse kinematics and path planning for redundant manipulators ［C］.Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006. IEEE, 2006: 1874-1879.
［66］ Kuffner J J, LaValle S M. RRTconnect: An efficient approach to singlequery path planning ［C］. Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No 00CH37065). IEEE, 2000, 2: 995-1001.
［67］谢碧云, 赵京, 刘宇. 基于快速扩展随机树的7R机械臂避障达点运动规划［J］. 机械工程学报, 2012, 48(3): 63-69.
Xie Biyun, Zhao Jing, Liu Yu. Motion planning of reaching point movements for 7R robotic manipulators in obstacle environment based on rapidlyexploring random tree algorithm ［J］. Journal of Mechanical Engineering, 2012, 48(3): 63-69.
［68］ GómezBravo F, Carbone G, Fortes J C. Collision free trajectory planning for hybrid manipulators ［J］. Mechatronics, 2012, 22(6): 836-851.
［69］ Solovey K, Salzman O, Halperin D. Finding a needle in an exponential haystack: Discrete RRT for exploration of implicit roadmaps in multirobot motion planning ［M］. Algorithmic Foundations of Robotics XI. Springer, Cham, 2015: 591-607.
［70］ Zhang H, Wang Y, Zheng J, et al. Path planning of industrial robot based on improved RRT algorithm in complex environments ［J］. IEEE Access, 2018, 6: 53296-53306.
［71］ Ye L, Duan J, Yang Z, et al. Collisionfree motion planning for the litchipicking robot ［J］. Computers and Electronics in Agriculture, 2021, 185: 106151.
［72］马慧丽, 鲁照权, 王寿庭. 基于改进RRT*算法的机械臂路径规划研究［J］. 机械设计与研究, 2020, 36(4): 42-46.
Ma Huili, Lu Zhaoquan, Wang Shouting. Research on manipulator path planning based on improved RRT* algorithms ［J］. Machine Design & Research, 2020, 36(4): 42-46.
［73］张勤, 乐晓亮, 李彬, 等. 基于CTBRRT*算法的采摘机械臂运动路径规划［J/OL］. 农业机械学报: 1-10［2021-08-10］. http://kns.cnki.net/kcms/detail/11.1964.S.20210719.1403.014.html.
Zhang Qin, Le Xiaoliang, Li Bin,et al. Motion path planning of picking manipulator based on CTBRRT* algorithm ［J/OL］. Transactions of the Chinese Society for Agricultural Machinery: 1-10［2021-08-10］. http://kns.cnki.net/kcms/detail/11.1964.S.20210719.1403.014.html.
［74］张荣霞, 武长旭, 孙同超, 等. 深度强化学习及在路径规划中的研究进展［J/OL］. 计算机工程与应用: 1-15［2021-08-23］. http://kns.cnki.net/kcms/detail/11.2127.tp.20210714.1447.008.html.
Zhang Rongxia, Wu Changxu, Sun Tongchao, et al. Deep reinforcement learning and its application in path planning ［J/OL］. Computer Engineering and Applications: 1-15［2021-08-23］. http://kns.cnki.net/kcms/detail/11.2127.tp.20210714.1447.008.html.
［75］ Mnih V, Kavukcuoglu K, Silver D, et al. Playing Atari with deep reinforcement learning ［J］. arXiv preprint arXiv: 1312.5602, 2013.
［76］刘全, 翟建伟, 章宗长, 等. 深度强化学习综述［J］. 计算机学报, 2018, 41(1): 1-27.
Liu Quan, Zhai Jianwei, Zhang Zongchang,et al. A survey on deep reinforcement learning ［J］. Chinese Journal of Computers, 2018, 41(1): 1-27.
［77］ Anschel O, Baram N, Shimkin N. AveragedDQN: Variance reduction and stabilization for deep reinforcement learning ［C］. International Conference on Machine Learning. PMLR, 2017: 176-185.
［78］熊俊涛, 李中行, 陈淑绵, 等. 基于深度强化学习的虚拟机器人采摘路径避障规划［J］. 农业机械学报, 2020, 51(S2): 1-10.
Xiong Juntao, Li Zhongxing, Chen Shumian, et al. Obstacle avoidance planning of virtual robot picking path based on deep reinforcement learning ［J］. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51(S2): 1-10.
［79］ Lin G, Zhu L, Li J, et al. Collisionfree path planning for a guavaharvesting robot based on recurrent deep reinforcement learning ［J］. Computers and Electronics in Agriculture, 2021, 188: 106350.

[1]	陈文明, , 胡良龙, 袁建宁, 王公仆, 王冰, 吴稳, . 国内蔬菜收获机自动控制技术研究现状及展望国内蔬菜收获机自动控制技术研究现状及展望[J]. 智能化农业装备学报（中英文）, 2021, 2(2): 57-63.
[2]	刘勤, 胡良龙, 郑砚砚, 檀律科, 王叶萌, 陈青. 中国茶叶及蔬菜智能化收获技术发展现状^*[J]. 智能化农业装备学报（中英文）, 2021, 2(1): 20-27.