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Influence of Network Delay on QoS Control Using Neural Network in Remote Robot Systems with Force Feedback

Authors:

YUTAKA ISHIBASHI,

HISTOSHI WATANABEAuthors Info & Claims

ICNCC '20: Proceedings of the 2020 9th International Conference on Networks, Communication and Computing

Pages 104 - 111

https://doi.org/10.1145/3447654.3447669

Published: 13 May 2021 Publication History

Abstract

In this paper, we focus on the application of big data, cloud computing, and AI (Artificial Intelligence) to QoS (Quality of Service) control to remote robot systems with force feedback. As the first step of our research, we investigate the influence of cloud delay on the remote robot systems while using big data, cloud computing, and AI technology by experiment. In the experiment, we deal with a task in which two robot arms of the two remote robot systems grasp an object and carry the object together. By using big data, cloud computing, and neural network, we predict the optimum value for the robot position control using force information, which we previously proposed as QoS control, in the system, and investigate the influence of cloud delay. Experimental results show that our method is effective, and the feedback force becomes larger as the delay increases.

References

[1]

K. Ohnishi, “Real world haptics: Its principle and future prospects,” (in Japanese), The journal of the Institute of Electrical Engineers of Japan (IEEJ), vol. 133, no. 5, pp. 268–269, Mar. 2013.

[2]

T. Kawai, “Haptics for surgery,” (in Japanese), The journal of the Institute of Electrical Engineers of Japan (IEEJ), vol. 133, no.5, pp. 282–285, Mar. 2013.

[3]

T. Miyoshi and K. Terashima, “A Stabilizing Method for Non-Passive Force-Position Teleoperating System,” The 35th Control Theory Symposium, vol.35, pp. 127–130, Sep. 2006.

[4]

P. Huang, T. Miyoshi, and Y. Ishibashi, “Enhancement of stabilization control in remote robot system with force feedback,” International Journal of Communications, Network and System Sciences (IJCNS), vol. 12, no. 7, pp. 99-111, July 2019.

[5]

Q. Qian, Y. Ishibashi, P. Huang, and Y. Tateiwa, “Assessment of force perception in remote robot system with haptics,” IEICE Society Conference, BS-7-22, Sep. 2018.

[6]

K. Suzuki, Y. Maeda, Y. Ishibashi, and N. Fukushima, “Improvement of operability in remote robot control with force feedback,” in Proc. IEEE Global Conference on Consumer Electronics (GCCE), pp. 16–20, Oct. 2015.

[7]

S. Ishikawa, Y. Ishibashi, P. Huang, and Y. Tateiwa, “Effect of robot position control with force information for cooperative work between remote robot systems,” in Proc. The 2nd World Symposium on Communication Engineering (WSCE), pp. 210-214, Dec. 2019.

[8]

Y. Ishibashi and S. Tasaka, “Application QoS management for distributed multimedia systems and its implementation,” (in Japanese), The Journal of Institute of Electronics, Information and Communication Engineers (IEICE), vol. 87, no. 3, pp. 220-226, Mar. 2004.

[9]

T. Abe, Y. Ishibashi, H. Yoshino, “State of the art of service quality,” The Institute of Electronics, Information and Communication Engineers (IEICE), vol. 91, no. 2, pp. 88-86, Feb. 2008.

[10]

I. A. T. Hashem, I. Yaqoob, N. B. Anuar, S. Mokhtar, A. Gani, and S. U. Khan, “The rise of ‘big data’ on cloud computing: Review and open research issues,” Information Systems, vol. 47, pp. 98-115, Jan. 2015.

Digital Library

[11]

V. A. Memos, K. E. Psannis, Y. Ishibashi, B. G. Kim, and B. B. Gupta, “An efficient algorithm for media-based surveillance system (EAMSuS) in IoT smart city framework,” Future Generation Computer System, vol. 83, pp. 619-628, 2018.

Digital Library

[12]

A. Ramesh, C. Kambhampati, J. Monson and P. Drew, “Artificial intelligence in medicine,” Annals of The Royal College of Surgeons of England, vol. 86, pp. 334–338, Oct. 2004.

[13]

S. Nii, T. Okuda, and Y. Ishibashi, “A performance evaluation of queueing systems with finite capacity by machine learning,” (in Japanese), IEICE Technical Report, IN2018-75 Jan. 2019

[14]

L. K. Hansen and P. Salamon, “Neural network ensembles,” IEEE Transactions on pattern analysis and machine intelligence, vol. 12, no. 10, Oct. 1990.

Digital Library

[15]

S. Dreiseitl and L. Ohno-Machadob, “Logistic regression and artificial neural network classification models: a methodology review,” Journal of Biomedical Informatics, vol. 35, issues 5–6, pp. 352-359, Oct. 2002.

Digital Library

[16]

Y. Ishibashi, E. Taguchi, P. Huang, and Y. Tateiwa, “Robot position control with force information in cooperation between remote robot system,” in Proc. The 5th International Conference on Control, Automation and Robotics (ICCAR), Apr. 2019.

[17]

S. Ishikawa, Y. Ishibashi, P. Huang, and Y. Tateiwa, “Robot position control using force information in remote robot systems with force feedback,” (in Japanese), IEICE Technical Report, CQ2019-34, July 2019.

[18]

3D Systems Touch, https://www.3dsystems.com/haptics-devices/touch.

[19]

RV-2F-D Series Standard Specifications, http://dl.mitsubishielectric.co.jp/dl/fa/members/document/manual/robot/bfp-a8899 /bfp-a8899u.pdf.

[20]

CR75-/CR751 Controller instruction manual force sensing function, http://dl.mitsubishielectric.co.jp/dl/fa/members/document/manual/robot/bfp-a8940/bfp-a8940Z.pdf.

[21]

CRn-500 Series ethernet interface manual, http://dl.mitsubishielectric.co.jp/dl/fa/members/document/ manual/robot/bfp-a8080/bfp-a8080e.pdf.

Cited By

Win KIshibashi YWin K(2024)Influence of Local Lag on Reaction Force in Networked Virtual Environment with Haptic Sense2024 IEEE Conference on Computer Applications (ICCA)10.1109/ICCA62361.2024.10533043(1-6)Online publication date: 16-Mar-2024
https://doi.org/10.1109/ICCA62361.2024.10533043
Win KIshibashi YWin K(2024)QoE Assessment of Cooperative Work in Networked Virtual Reality Environment with Haptic Sense: Influence of Network LatencyAdvances in Information Communication Technology and Computing10.1007/978-981-97-6103-6_6(69-83)Online publication date: 2-Oct-2024
https://doi.org/10.1007/978-981-97-6103-6_6
Huang PIshibashi Y(2023)Perspective Chapter: Cooperation among Humans and Robots in Remote Robot Systems with Force FeedbackHuman-Robot Interaction - Perspectives and Applications10.5772/intechopen.106951Online publication date: 10-May-2023
https://doi.org/10.5772/intechopen.106951
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ICNCC '20: Proceedings of the 2020 9th International Conference on Networks, Communication and Computing

December 2020

157 pages

ISBN:9781450388566

DOI:10.1145/3447654

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 13 May 2021

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ICNCC 2020

ICNCC 2020: 2020 The 9th International Conference on Networks, Communication and Computing

December 18 - 20, 2020

Tokyo, Japan

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Cited By

Win KIshibashi YWin K(2024)Influence of Local Lag on Reaction Force in Networked Virtual Environment with Haptic Sense2024 IEEE Conference on Computer Applications (ICCA)10.1109/ICCA62361.2024.10533043(1-6)Online publication date: 16-Mar-2024
https://doi.org/10.1109/ICCA62361.2024.10533043
Win KIshibashi YWin K(2024)QoE Assessment of Cooperative Work in Networked Virtual Reality Environment with Haptic Sense: Influence of Network LatencyAdvances in Information Communication Technology and Computing10.1007/978-981-97-6103-6_6(69-83)Online publication date: 2-Oct-2024
https://doi.org/10.1007/978-981-97-6103-6_6
Huang PIshibashi Y(2023)Perspective Chapter: Cooperation among Humans and Robots in Remote Robot Systems with Force FeedbackHuman-Robot Interaction - Perspectives and Applications10.5772/intechopen.106951Online publication date: 10-May-2023
https://doi.org/10.5772/intechopen.106951
Huang PIshibashi Y(2021)QoS Control in Remote Robot Operation with Force FeedbackRobotics Software Design and Engineering10.5772/intechopen.97011Online publication date: 15-Sep-2021
https://doi.org/10.5772/intechopen.97011
Zhang YHuang PIshibashi YOkuda TPsannis K(2021)Effect of Neural Network on Robot Position Control Using Force Information2021 IEEE 9th International Conference on Information, Communication and Networks (ICICN)10.1109/ICICN52636.2021.9673826(545-549)Online publication date: 25-Nov-2021
https://doi.org/10.1109/ICICN52636.2021.9673826
Wang XHuang PIshibashi YOkuda T(2021)Robot Position Control Using Force Information by Neural Network in Remote Robot Systems2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)10.1109/ICCE-TW52618.2021.9602989(1-2)Online publication date: 15-Sep-2021
https://doi.org/10.1109/ICCE-TW52618.2021.9602989

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