Abstract
Objective: Solve the problem of low accuracy of collaborative robots in food dynamic target grasping at present. Methods: Based on the architecture of collaborative robots, a combination of fuzzy self-tuning PID control and robust adaptive compensator was proposed for collaborative robot food dynamic target grasping. PID combined with fuzzy control to achieve parameter self-tuning, and robust algorithm combined with adaptive algorithm for system uncertainty compensation. The performance of the proposed method was analyzed through experiments, verifying its feasibility. Results: The proposed method had good results in the dynamic target grasping of collaborative robots, improving the accuracy of dynamic grasping. At a conveyor belt speed of 100 mm/s, the success rate of dynamic grasping reaches 99.50%, which had certain application value for food dynamic target grasping. Conclusion: By optimizing existing target grasping control methods, the grasping accuracy of collaborative robots can be effectively improved.
Publication Date
1-30-2024
First Page
95
Last Page
100
DOI
10.13652/j.spjx.1003.5788.2023.60127
Recommended Citation
Pengfei, CHENG; Mingtang, LIU; and Chen, SUN
(2024)
"Research on dynamic target grasping control method for food collaborative robot,"
Food and Machinery: Vol. 40:
Iss.
1, Article 14.
DOI: 10.13652/j.spjx.1003.5788.2023.60127
Available at:
https://www.ifoodmm.cn/journal/vol40/iss1/14
References
[1] 吴高华, 杨依领, 李国平, 等. 具有高位移增幅特性的柔顺并联式微动平台[J]. 机器人, 2020, 42（1）: 1-9.
WU G H, YANG Y L, LI G P, et al. Compliant parallel micro motion platform with high displacement and amplitude increase characteristics[J]. Robot, 2020, 42（1）: 1-9.
[2] 刘海龙, 张蕾, 吴海波. 基于双视觉引导的工业机器人立体定位技术的研究[J]. 电气自动化, 2021, 43（1）: 116-118.
LIU H L, ZHANG L, WU H B. Research on stereo positioning technology of industrial robot based on dual vision guidance[J]. Electrical Automation, 2021, 43（1）: 116-118.
[3] 曾劲松, 薛文凯, 徐博凡, 等. 双目视觉引导机器人定位抓取技术的研究[J]. 组合机床与自动化加工技术, 2019, 12（1）: 131-137.
ZENG J S, XUE W K, XU B F, et al. Research on positioning and grasping technology of binocular vision guided robot[J]. Modular Machine Tools & Automatic Machining Technology, 2019, 12（1）: 131-137.
[4] 林义忠, 陈旭. 基于机器视觉的机器人定位抓取的研究进展[J]. 自动化与仪器仪表, 2021, 11（3）: 9-12.
LIN Y Z, CHEN X. Research progress of robot positioning and grasping based on machine vision[J]. Automation and Instrumentation, 2021, 11（3）: 9-12.
[5] 贾超广, 肖海霞. 机器视觉的食品包装快速分拣系统[J]. 食品工业, 2021, 42（5）: 276-279.
JIA C G, XIAO H X. Rapid sorting system for food packaging based on machine vision[J]. Food Industry, 2021, 42（5）: 276-279.
[6] 王敏, 蒋金伟, 曹彦陶. 基于改进粒子群的食品分拣机器人动态目标抓取控制方法[J]. 食品与机械, 2022, 38（3）: 86-91.
WANG M, JIANG J W, CAO Y T. A dynamic target grasping control method for food sorting robot based on improved particle swarm optimization[J]. Food & Machinery, 2022, 38（3）: 86-91.
[7] 肖瑶星, 刘立新, 胡柳, 等. 基于三维模型的食品分拣机器人抓取控制方法[J]. 食品与机械, 2023, 39（4）: 77-82, 162.
XIAO Y X, LIU L X, HU L, et al. Grab control method for food sorting robot based on 3D model[J]. Food & Machinery, 2023, 39（4）: 77-82, 162.
[8] 柳振宇, 薛毓强, 谢祖强. 基于闭环和前馈控制的高速食品分拣机器人控制技术[J]. 食品与机械, 2021, 37（7）: 87-93.
LIU Z Y, XUE Y Q, XIE Z Q. Control technology of high-speed food sorting robot based on closed-loop andfeedforward control[J]. Food & Machinery, 2021, 37（7）: 87-93.
[9] 李世裴, 韩家哺, 路博凡, 等. 视觉引导下协作机器人抓取技术研究[J]. 重庆工商大学学报（自然科学版）, 2022, 39（1）: 42-48.
LI S P, HAN J P, LU B F, et al. Research on visual guided collaborative robot grasping technology[J]. Journal of Chongqing Business University （Natural Science Edition）, 2022, 39（1）: 42-48.
[10] 胡国喜, 王超, 刘宇珩. 基于改进光滑滑模阻抗控制的水果分拣机械人夹持机构控制方法[J]. 食品与机械, 2021, 37（2）: 130-134.
HU G X, WANG C, LIU Y H. Acontrol method for fruit sorting robot clamping mechanism based on improved smooth sliding mode impedance control[J]. Food & Machinery, 2021, 37（2）: 130-134.
[11] 饶期捷, 黄海松, 张松松, 等. 基于机器视觉的Baxter机器人抓取算法研究[J]. 组合机床与自动化技术加工, 2021, 12（9）: 1-5.
RAO Q J, HUANG H S, ZHANG S S, et al. Research on baxter robot grab algorithm based on machine vision[J]. Modular Machine Tools & Automation Technology Processing, 2021, 12（9）: 1-5.
[12] 赵利平, 吴德刚. 融合GA的三点定位夜间苹果目标的识别算法研究[J]. 中国农机化学报, 2020, 41（5）: 134-138.
ZHAO L P, WU D G. Research on recognition algorithm of three-point positioning night apple target based on GA[J]. China Agricultural Machinery Chemical Journal, 2020, 41（5）: 134-138.
[13] 朱建宝, 许志龙, 孙玉玮, 等. 基于 OpenPose 人体姿态识别的变电站危险行为检测[J]. 自动化与仪表, 2020, 35（2）: 47-51.
ZHU J B, XU Z L, SUN Y W, et al. Detection of dangerous behaviors in substations based on OpenPose human posture recognition[J]. Automation and Instrumentation, 2020, 35（2）: 47-51.
[14] 于文妍, 杨坤林. 四旋翼无人机串级模糊自适应PID控制系统设计[J]. 机械设计与制造, 2019, 12（1）: 227-231.
YU W Y, YANG K L. Design of cascade fuzzy adaptive PID control system for four rotor UAV[J]. Mechanical Design & Manufacturing, 2019, 12（1）: 227-231.
[15] 陶浩, 李笑, 陈敏. 基于改进ORB特征的遥操作工程机器人双目视觉定位[J]. 测控技术, 2019, 38（7）: 19-23.
TAO H, LI X, CHEN M. binocular vision ofteleoperation engineering robot based on improved orb feature[J]. Measurement and Control Technology, 2019, 38（7）: 19-23.
[16] 宋海涛, 何文浩, 原魁. 一种基于SIFT特征的机器人环境感知双目立体视觉系统[J]. 控制与决策, 2019, 34（7）: 1 545-1 552.
SONG H T, HE W H, YUAN K. A robot environment perception binocular stereo vision system based on SIFT feature[J]. Control and Decision, 2019, 34（7）: 1 545-1 552.
[17] 马伟苹, 李文新, 孙晋川, 等. 基于粗—精立体匹配的双目视觉目标定位方法[J]. 计算机应用, 2020, 40（1）: 227-232.
MA W P, LI W X, SUN J C, et al. Binocular vision target location method based on coarse fine stereo matching[J]. Computer Applications, 2020, 40（1）: 227-232.
[18] 罗久飞, 邱广, 张毅, 等. 基于自适应双阈值的SURF双目视觉匹配算法研究[J]. 仪器仪表学报, 2020, 41（3）: 240-247.
LUO J F, QIU G, ZHANG Y, et al. Research on SURF binocular vision matching algorithm based on adaptive double threshold[J]. Journal of Instrumentation, 2020, 41（3）: 240-247.
[19] 程禹, 王晓华, 王文杰, 等. 基于改进AKAZE算法的图像特征匹配方法[J]. 西安工程大学学报, 2020, 34（8）: 51-56.
CHENG Y, WANG X H, WANG W J, et al. Image feature matching method based on improved AKAZE algorithm[J]. Journal of Xi'an Engineering University, 2020, 34（8）: 51-56.
[20] 苏婷婷, 张好剑, 王云宽, 等. 基于费拉里法的Delta机器人动态目标抓取算法[J]. 华中科技大学学报（自然科学版）, 2018, 46（6）: 128-132.
SU T T, ZHANG H J, WANG Y K, et al. Delta robot dynamic target grasping algorithm based on Ferrari method[J]. Journal of Huazhong University of science and Technology （Natural Science Edition）, 2018, 46（6）: 128-132.
[21] 陶永, 兰江波, 刘海涛, 等. 基于滑模和模糊算法相融合的人机协作机器人轨迹跟踪方法[J]. 机械工程学报, 2022, 58（18）: 181-191.
TAO Y, LAN J B, LIU H T, et al. A trajectory tracking method for human-machine collaborative robots based on the fusion of sliding mode and fuzzy algorithm[J]. Journal of Mechanical Engineering, 2022, 58（18）: 181-191.