Abstract
The survey found that during table tennis training there are often many scattered balls that need to be picked up manually, affecting the efficiency of the players’ training. Currently, table tennis is picked up manually using a table tennis picker. In this paper, delta omnidirectional wheeled table tennis automatic pickup robot based on the vision servo achieves fully automatic table tennis pickup by combining the characteristics and requirements of table tennis sports. In this paper, we design a vision algorithm for a table tennis automatic pickup robot system, give a kinematic inverse solution for the delta omnidirectional wheel, complete the design of the robot control system, and build the platform for the experiment. A pickup experiment is conducted on scattered ping-pong balls of different colors. Experiments have shown that the robot can safely clean up scattered table tennis balls on the table tennis field with high positioning accuracy and top pick up rate. It is proved that the robot designed in this paper has extensive application value and prospects.
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Refrences
Hayakawa, Y., Nakashima, A., Itoh, S., et al.: Ball trajectory planning in serving task for table tennis robot. SICE J. Control Meas. Syst. Int. 9(2), 50–59 (2016)
Zhang, K., Cao, Z., Liu, J., et al.: Real-time visual measurement with opponent hitting behavior for table tennis robot. IEEE Trans. Instrum. Meas. 67(4), 811–820 (2018)
Liu, Y., Liu, L.: Accurate real-time ball trajectory estimation with onboard stereo camera system for humanoid ping-pong robot. Robot. Auton. Syst 101, 34–44 (2018)
Lin, H.I., Huang, Y.C.: Ball trajectory tracking and prediction for a ping-pong robot. In: 2019 9th International Conference on Information Science and Technology. pp. 222–227, IEEE (2019)
Gu, S., Chen, X., Zeng, W., et al.: A deep learning tennis ball collection robot and the implementation on nvidia jetson tx1 board. In: 2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. pp. 170–175,. IEEE (2018)
Pinto, R.M., Becker, M., Tronco, M.L.: Sweet citrus fruit detection in thermal images using fuzzy image processing. In: Applications of Computational Intelligence: Second IEEE Colombian Conference, ColCACI 2019, Barranquilla, Colombia, June 5–7, Revised Selected Papers. Springer Nature (2019)
Wang, Y., Cheng, G.: Application of gradient-based Hough transform to the detection of corrosion pits in optical images. Appl. Surface Sci. 366, 9–18 (2016)
He, K., Hu, Y.P.: An improved method of hough transform for circle recognition based on optimized gradient. In: 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology. Atlantis Press (2017)
Calatroni, L., van Gennip, Y., Schönlieb, C.B., et al.: Graph clustering, variational image segmentation methods and Hough transform scale detection for object measurement in images. J.  Math. Imaging Vis. 57(2), 269–291 (2017)
Solsona, S.P., Maeder, M., Tauler, R., et al.: A new matching image preprocessing for image data fusion. Chemom. Intell. Lab. Syst. 164, 32–42 (2017)
Ayyıldız, M., Çetinkaya, K.: Comparison of four different heuristic optimization algorithms for the inverse kinematics solution of a real 4-DOF serial robot manipulator. Neural Comput. Appl. 27(4), 825–836 (2016)
Zhang, Y., Huang, H., Yan, X., et al.: Inverse-free solution to inverse kinematics of two-wheeled mobile robot system using gradient dynamics method. In: 2016 3rd International Conference on Systems and Informatics (ICSAI). pp. 126–132, IEEE (2016)
Zhang, J., Yang, S.A.: Novel PSO algorithm based on an incremental-PID-controlled search strategy. Soft. Comput. 20(3), 991–1005 (2016)
Eltag, K., Aslamx, M.S., Ullah, R.: Dynamic stability enhancement using fuzzy PID control technology for power system. Int. J. Control Autom. Syst. 17(1), 234–242 (2019)
El-Samahy, A.A., Shamseldin, M.A.: Brushless DC motor tracking control using self-tuning fuzzy PID control and model reference adaptive control. Ain Shams Eng. J. 9(3), 341–352 (2018)
Acknowledgement
This research was funded by the National Natural Science Foundation of China (grant number 61672226, 61903137). This research was funded by the Natural Science Foundation of Hunan Province (grant number 2020JJ4316).
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Lu, M., Wang, C., Wang, J., Duan, H., Sun, Y., Chen, Z. (2021). Delta Omnidirectional Wheeled Table Tennis Automatic Pickup Robot Based on Vision Servo. In: Liu, Q., Liu, X., Shen, T., Qiu, X. (eds) The 10th International Conference on Computer Engineering and Networks. CENet 2020. Advances in Intelligent Systems and Computing, vol 1274. Springer, Singapore. https://doi.org/10.1007/978-981-15-8462-6_60
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DOI: https://doi.org/10.1007/978-981-15-8462-6_60
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