Welcome to Scholar Publishing Group

International Journal of Multimedia Computing, 2022, 3(1); doi: 10.38007/IJMC.2022.030105.

Remote Operating System of Picking Robot Based on Big Data and WiFi

Author(s)

Fang Li

Corresponding Author:
Fang Li
Affiliation(s)

Department of Information Engineering, Heilongjiang International University, Heilongjiang, China

Abstract

Fruit picking robots can automate fruit picking operations and solve the problems of labor shortage and high cost. Therefore, research on fruit picking robots is of great significance to reduce the cost of fruit picking. Here we mainly study the remote operating system based on big data and WiFi picking robot. This article first introduces the principles and architecture of big data Hadoop technology, then designs the picking robot motion model and positioning navigation model, and implements the picking robot positioning and navigation algorithm, and finally introduces the overall scheme and hardware design of the picking robot remote operating system. In this paper, a comparative study of the fruit stalk recognition method based on contour constraints and regional growth is conducted. The fruit stalk segmentation algorithm based on the region growth method can achieve fruit stalk segmentation under different lighting conditions, and the correct recognition rate of fruit stalks is 92.5%. The binding variable is the calculation of the color difference and color components of the target area of the fruit stem first. Under the conditions of direct light and backlighting and shading, the threshold of the fruit stem has a certain difference. There is a risk that the threshold selection is not accurate enough. The average correct recognition error is 87.4%. The experimental results show that the remote operating system can accurately control the movement of the picking robot in the middle of the fruit tree through the steering and movement control of the picking robot to successfully complete the picking operation, which meets the design requirements and has certain reference significance for the remote control of the picking robot.

Keywords

Big Data, Picking Robot, Remote Operating System, Hadoop

Cite This Paper

Fang Li. Remote Operating System of Picking Robot Based on Big Data and WiFi. International Journal of Multimedia Computing (2022), Vol. 3, Issue 1: 29-42. https://doi.org/10.38007/IJMC.2022.030105.

References

[1] Peng H, Huang B, Shao Y, et al. General improved SSD model for picking object recognition of multiple fruits in natural environment. Transactions of the Chinese Society of Agricultural Engineering. (2018) 34(16): 155-162.

[2] Li G. Picking robot vision system based on a single-chip microcomputer. Agro Food Industry Hi Tech. (2017) 28(1): 1949-1952.

[3] Li D, Xu S, Zheng Y, et al. Navigation Path Detection for Cotton Field Operator Robot Based on Horizontal Spline Segmentation. International Journal of Information Technology & Web Engineering. (2018) 12(3): 28-41. https://doi.org/10.4018/IJITWE.2017070103

[4] Bardewa S, Hendrickson S. 3-D Object Segmentation and Recognition Object Grasping by a Humanoid Robot. Circuit Cellar. (2017) 320: 10-17.

[5] Wang Y, Jiao Y, Xiong R, et al. MASD: A Multimodal Assembly Skill Decoding System for Robot Programming by Demonstration. IEEE Transactions on Automation ence & Engineering. (2018) PP (4): 1-13. https://doi.org/10.1109/TASE.2017.2783342

[6] Krug R, Stoyanov T, Tincani V, et al. The Next Step in Robot Commissioning: Autonomous Picking and Palletizing. IEEE Robotics & Automation Letters. (2017) 1(1): 546-553. https://doi.org/10.1109/LRA.2016.2519944

[7] Hu X, Pan Z, Lv S. Picking Path Optimization of Agaricus bisporus Picking Robot. Mathematical Problems in Engineering. (2019) 2019(7): 1-16. https://doi.org/10.1155/2019/8973153

[8] Lv G. High-speed Parallel Automatic Control Dynamic Modeling of Picking Robot Based on PLC. IPPTA: Quarterly Journal of Indian Pulp and Paper Technical Association. (2018) 30(6): 796-802.

[9] Puchert T. Bin-Picking mit Handlingrobotern. Elektrotechnische Zeitschrift. (2017) 138(6): 62-64.

[10] A L M, A G C, B Y L, et al. Design and simulation of an integrated end-effector for picking kiwifruit by robot. Information Processing in Agriculture. (2020) 7(1): 58-71. https://doi.org/10.1016/j.inpa.2019.05.004

[11] Harada K, Wan W, Tsuji T, et al. Experiments on Learning Based Industrial Bin-picking with Iterative Visual Recognition. Industrial Robot. (2018) 45(4): 446-457. https://doi.org/10.1108/IR-01-2018-0013

[12] Iversen T F, Ellekilde L P. Benchmarking motion planning algorithms for bin-picking applications. Industrial Robot. (2017) 44(2): 189-197. https://doi.org/10.1108/IR-06-2016-0166

[13] Jia Y, Du J, Zhang W, et al. [Lecture Notes in Electrical Engineering] Proceedings of 2016 Chinese Intelligent Systems Conference Volume 405 Research on Grasp Force Control of Apple-Picking Robot Based on Improved Impedance Control. (2016) 10.1007/978-981-10-2335-4(Chapter 13): 133-142. https://doi.org/10.1007/978-981-10-2335-4_13

[14] Madslien J. Robots enter the chicken shed. Professional engineering. (2017) 30(5): 7-7.

[15] Niu L, Zhou W, Wang D, et al. Extracting the symmetry axes of partially occluded single apples in natural scene using convex hull theory and shape context algorithm. Multimedia Tools & Applications. (2017) 76(12): 14075-14089. https://doi.org/10.1007/s11042-016-3781-8

[16] Moriya Y, Tanaka D, Yamazaki K, et al. A method of picking up a folded fabric product by a single-armed robot. ROBOMECH Journal. (2018) 5(1): 1-12. https://doi.org/10.1186/s40648-017-0098-y

[17] Ojha S R, Das S, Karanjit S. A Process Ontology for a Confectionery Service Robot. International Journal of Semantic Computing. (2018) 12(01): 149-166. https://doi.org/10.1142/S1793351X18400081

[18] Subscribers Only. Study on design of apple harvesting robots and its control algorithm based on disturbance observer. Revista De La Facultad De Ingenieria. (2017) 32(3): 575-584.

[19] Tang Y, Li L, Feng W, et al. Recycled aggregate concrete-filled steel column convex deformation detection via non-contact measurement. UPB entific Bulletin, Series D: Mechanical Engineering. (2017) 79(4): 67-82.

[20] Kaipa K N, Kankanhalli-Nagendra A S, Kumbla N B, et al. Addressing perception uncertainty induced failure modes in robotic bin-picking. Robotics and Computer Integrated Manufacturing. (2016) 42(dec.): 17-38. https://doi.org/10.1016/j.rcim.2016.05.002

[21] Kaczmarek W, Borys S. Algorytm tworzenia aplikacji sortowania/pakowania z wykorzystaniem programu PickMaster 3 dla robotów firmy ABB. Mechanik. (2018) 91(7): 526-528. https://doi.org/10.17814/mechanik.2018.7.73

[22] Babin V, Gosselin C. Picking, grasping, or scooping small objects lying on flat surfaces: A design approach. The International journal of robotics research. (2018) 37(12): 1484-1499. https://doi.org/10.1177/0278364918802346

[23] Morandotti L. Robot Collaborativo e intelligente. Plastix. (2017) 40(2): 96-97.

[24] Wada K, Sugiura M, Yanokura I, et al. Pick-and-verify: verification-based highly reliable picking system for various target objects in clutter. Advanced Robotics. (2017) 31(6): 311-321. https://doi.org/10.1080/01691864.2016.1269672

[25] Boschetti Giovanni. A Picking Strategy for Circular Conveyor Tracking. Journal of Intelligent & Robotic Systems. (2016) 81(2): 241-255. https://doi.org/10.1007/s10846-015-0242-y

[26] Correll Nikolaus, Bekris Kostas E, Berenson Dmitry. Analysis and Observations from the First Amazon Picking Challenge. IEEE Transactions on Automation ence & Engineering. (2018) 15(1): 172-188. https://doi.org/10.1109/TASE.2016.2600527

[27] Su J, Liu Z Y, Qiao H, et al. Pose-estimation and reorientation of pistons for robotic bin-picking. Industrial Robot-An International Journal. (2015) 43(1): 22-32. https://doi.org/10.1108/IR-06-2015-0129

[28] Pereira N, Ribeiro A F, Lopes G, et al. Path planning towards non-compulsory multiple targets using TWIN-RRT. Industrial Robot. (2016) 43(4): 370-379. https://doi.org/10.1108/IR-02-2016-0069