Proceedings of International Conference on Applied Innovation in IT
2020/03/10, Volume 8, Issue 1, pp.87-94

Robotic System Position Control Algorithm Based on Target Object Recognition

Pavel Slivnitsin, Andrey Bachurin, Leonid Mylnikov

Abstract: Creation of robotic systems capable of manipulating objects of the real world is an actual problem allowing both raising labor efficiency and reducing traumatism risk for a person. In the paper, the task of large-node replacement of the outdoor lighting luminaires with the use of robotic system is considered. For this, the accompanying tasks connected with the object (luminaire) identification and positioning of robot gripper concerning object have been solved. The resulting algorithms allow us to solve tasks in conditions of varying visibility, different backgrounds, overlapping objects, if necessary, positioning on certain parts of the target object. They can be used to identify of any elongated shape objects after appropriate training of the neural network. These algorithms allow us to position the robot arm in such a way that it can take the necessary object with the help of the gripper. The practical significance of the solved problem is connected with the possibility of robotics systems practical application in the human environment and the creation of anthropomorphic robots.

Keywords: Pattern Recognition, Image Recognition, Object Detection, Neural Network, Robotic System, Identification, Self-Positioning

DOI: 10.25673/32765

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  1. A. Dudarev, “The Problem Sensitization RoboticComplex Drilling and Milling of Sandwich Shellsof Polymer Composites,” Proc. 4Th Int. Conf.Appl. Innov., vol. 4, no. March, 2016, pp. 15-19.
  2. N. Pavlov, A. Bachurin, and E. Siemens,“Analysis of Outdoor Lighting Control Systemsand Devices for the Creation of Outdoor LightingAutomatic Control System Using the TrafficFlow Value,” Proc. Int. Conf. Appl. Innov. IT,no. March, 2017, pp. 95-100.
  3. P. Slivnitsin and A. Bachurin, “A modern way ofoutdoor lighting maintenance,” InternationalConference on Innovation Energy, 2019, J. Phys.:Conf. Ser. 1415 012010.
  4. А.А. Бачурин и П.А. Сливницин, “Соединительное устройство для монтажа и подключения светильника наружного освещения,”2695631, 2019.
  5. N. Dalal and B. Triggs, “Histograms of orientedgradients for human detection,” Proc. - 2005IEEE Comput. Soc. Conf. Comput. Vis. PatternRecognition, CVPR 2005, vol. I, no. 16, 2005, pp. 886-893.
  6. P. Viola and M. Jones, “Rapid Object Detectionusing a Boosted Cascade of Simple Features,” inProceedings IEEE Conf. on Computer Vision andPattern Recognition, pp. 511-518, 2001.
  7. L. Mylnikov, B. Krause, M. Kuetz, K. Bade and I.Shmidt, Intelligent data analysis in themanagement of production systems (approachesand methods), Shaker Verlag {GmbH}.
  8. V. Renò et al., “A SIFT-based software systemfor the photo-identification of the Risso’sdolphin,” Ecol. Inform., vol. 50, pp. 95-101, January 2019.
  9. N. Kumar et al., “Leafsnap: A computer visionsystem for automatic plant species identification,”in Lecture Notes in Computer Science (includingsubseries Lecture Notes in Artificial Intelligenceand Lecture Notes in Bioinformatics), vol. 7573LNCS, no. PART 2, 2012, pp. 502-516.
  10. H. Zhou, C. Yan and H. Huang, “Tree speciesidentification based on convolutional neuralnetworks,” in Proceedings - 2016 8thInternational Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2016, vol. 2, 2016, pp. 103-106.
  11. F. Al-Azzo, A. M. Taqi and M. Milanova,“Human related-health actions detection usingAndroid Camera based on TensorFlow ObjectDetection API,” Int. J. Adv. Comput. Sci. Appl.,vol. 9, no. 10, 2018, pp. 9-23.
  12. C. Szegedy et al., “Going deeper withconvolutions,” Proc. IEEE Comput. Soc. Conf.Comput. Vis. Pattern Recognit., vol. 07-12-June,pp. 1-9, June 2015.
  13. C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlensand Z. Wojna, “Rethinking the InceptionArchitecture for Computer Vision,” Proc. IEEEComput. Soc. Conf. Comput. Vis. PatternRecognit., vol. 2016-Decem, pp. 2818-2826, December 2016.
  14. “Tensorflow detection model zoo.” [Online].Available:
  15. S. Ravichandiran, Hands-On Meta Learning withPython: Meta learning using one-shot learning,MAML, Reptile, and Meta-SGD withTensorFlow. Packt Publishing Ltd.
  16. F. Chen, M. Selvaggio and D.G. Caldwell,“Dexterous Grasping by Manipulability Selectionfor Mobile Manipulator with Visual Guidance,”IEEE Trans. Ind. Informatics, vol. 15, no. 2,2019, pp. 1202-1210.
  17. H. Dong, E. Asadi, G. Sun, D. K. Prasad andI.M. Chen, “Real-Time Robotic Manipulation ofCylindrical Objects in Dynamic ScenariosThrough Elliptic Shape Primitives,” IEEE Trans.Robot., vol. 35, no. 1, 2019, pp. 95-113.
  18. C.H. Corbato, M. Bharatheesha, J. Van Egmond,J.Ju and M. Wisse, “Integrating different levelsof automation: Lessons from winning the amazonrobotics challenge 2016,” IEEE Trans. Ind.Informatics, vol. 14, no. 11, 2018, pp. 4916-4926.
  19. D. De Gregorio, R. Zanella, G. Palli, S. Pirozziand C. Melchiorri, “Integration of robotic visionand tactile sensing for wire-terminal insertiontasks,” IEEE Trans. Autom. Sci. Eng., vol. 16,no. 2, 2019, pp. 585-598.
  20. Z. Cao, N. Gu, J. Jiao, S. Nahavandi, C. Zhou andM.Tan, “A Novel Geometric TransportationApproach for Multiple Mobile Manipulators inUnknown Environments,” IEEE Syst. J., vol. 12,no. 2, 2018, pp. 1447-1455.
  21. A. Billard and D. Kragic, “Trends and challengesin robot manipulation,” Science (80), vol. 364,no. 6446, p. eaat8414, June 2019.
  22. A.M. Turing, “Computing machinery andintelligence,” Mind, vol. LIX, no. 236, 1950, pp. 433-460.



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