ČAS, Jure ;KLOBUČAR, Rok ;HERCOG, Darko ;ŠAFARIČ, Riko . Teleoperation of SCARA with Neural Network Based Controller. Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 54, n.2, p. 94-102, november 2017. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/article/teleoperation-of-scara-with-neural-network-based-controller/>. Date accessed: 23 dec. 2024. doi:http://dx.doi.org/.
Čas, J., Klobučar, R., Hercog, D., & Šafarič, R. (2008). Teleoperation of SCARA with Neural Network Based Controller. Strojniški vestnik - Journal of Mechanical Engineering, 54(2), 94-102. doi:http://dx.doi.org/
@article{.,
author = {Jure Čas and Rok Klobučar and Darko Hercog and Riko Šafarič},
title = {Teleoperation of SCARA with Neural Network Based Controller},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {54},
number = {2},
year = {2008},
keywords = {robotics; neutral network controller; remote experiment system; LabVIEW; MATLAB; Simulink; },
abstract = {This paper describes the development of neural network based controller for the teleoperation of Selective Compliance Assembly Robot Arm (SCARA). The SCARA is controlled and teleoperated via the internet. Presented experiment isused by students at the University of Maribor as a remote educational tool. Application is based on MATLAB/Simulink and LabVIEW software packages. MATLAB/Simulink and developed library DSP-2 Library for Simulink are used for neural network control algorithm development, simulation and code generation. The executable code is downloaded to the Digital Signal Processor (DSP). The DSP controls through the analog and digital I/O the real process and maintain the data connection with the laboratory server. The LabVIEW virtual instrument(VI) is used as a client server application for the teleoperation. LabVIEW VI provides the ability for parameter tuning, signal monitoring, on-line analysis and via Remote Panels technology also teleoperation by using the internet browser (Internet Explorer). The main advantage of a neural network controller is the exploitation of its self-learning capability. For example: when friction or an unexpected disturbance occurs, the user of a remote application does not need any information about the changed robot dynamics, because it is estimated independently of the remote user.},
issn = {0039-2480}, pages = {94-102}, doi = {},
url = {https://www.sv-jme.eu/article/teleoperation-of-scara-with-neural-network-based-controller/}
}
Čas, J.,Klobučar, R.,Hercog, D.,Šafarič, R. 2008 November 54. Teleoperation of SCARA with Neural Network Based Controller. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 54:2
%A Čas, Jure %A Klobučar, Rok %A Hercog, Darko %A Šafarič, Riko %D 2008 %T Teleoperation of SCARA with Neural Network Based Controller %B 2008 %9 robotics; neutral network controller; remote experiment system; LabVIEW; MATLAB; Simulink; %! Teleoperation of SCARA with Neural Network Based Controller %K robotics; neutral network controller; remote experiment system; LabVIEW; MATLAB; Simulink; %X This paper describes the development of neural network based controller for the teleoperation of Selective Compliance Assembly Robot Arm (SCARA). The SCARA is controlled and teleoperated via the internet. Presented experiment isused by students at the University of Maribor as a remote educational tool. Application is based on MATLAB/Simulink and LabVIEW software packages. MATLAB/Simulink and developed library DSP-2 Library for Simulink are used for neural network control algorithm development, simulation and code generation. The executable code is downloaded to the Digital Signal Processor (DSP). The DSP controls through the analog and digital I/O the real process and maintain the data connection with the laboratory server. The LabVIEW virtual instrument(VI) is used as a client server application for the teleoperation. LabVIEW VI provides the ability for parameter tuning, signal monitoring, on-line analysis and via Remote Panels technology also teleoperation by using the internet browser (Internet Explorer). The main advantage of a neural network controller is the exploitation of its self-learning capability. For example: when friction or an unexpected disturbance occurs, the user of a remote application does not need any information about the changed robot dynamics, because it is estimated independently of the remote user. %U https://www.sv-jme.eu/article/teleoperation-of-scara-with-neural-network-based-controller/ %0 Journal Article %R %& 94 %P 9 %J Strojniški vestnik - Journal of Mechanical Engineering %V 54 %N 2 %@ 0039-2480 %8 2017-11-03 %7 2017-11-03
Čas, Jure, Rok Klobučar, Darko Hercog, & Riko Šafarič. "Teleoperation of SCARA with Neural Network Based Controller." Strojniški vestnik - Journal of Mechanical Engineering [Online], 54.2 (2008): 94-102. Web. 23 Dec. 2024
TY - JOUR AU - Čas, Jure AU - Klobučar, Rok AU - Hercog, Darko AU - Šafarič, Riko PY - 2008 TI - Teleoperation of SCARA with Neural Network Based Controller JF - Strojniški vestnik - Journal of Mechanical Engineering DO - KW - robotics; neutral network controller; remote experiment system; LabVIEW; MATLAB; Simulink; N2 - This paper describes the development of neural network based controller for the teleoperation of Selective Compliance Assembly Robot Arm (SCARA). The SCARA is controlled and teleoperated via the internet. Presented experiment isused by students at the University of Maribor as a remote educational tool. Application is based on MATLAB/Simulink and LabVIEW software packages. MATLAB/Simulink and developed library DSP-2 Library for Simulink are used for neural network control algorithm development, simulation and code generation. The executable code is downloaded to the Digital Signal Processor (DSP). The DSP controls through the analog and digital I/O the real process and maintain the data connection with the laboratory server. The LabVIEW virtual instrument(VI) is used as a client server application for the teleoperation. LabVIEW VI provides the ability for parameter tuning, signal monitoring, on-line analysis and via Remote Panels technology also teleoperation by using the internet browser (Internet Explorer). The main advantage of a neural network controller is the exploitation of its self-learning capability. For example: when friction or an unexpected disturbance occurs, the user of a remote application does not need any information about the changed robot dynamics, because it is estimated independently of the remote user. UR - https://www.sv-jme.eu/article/teleoperation-of-scara-with-neural-network-based-controller/
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author = {Čas, J., Klobučar, R., Hercog, D., Šafarič, R.},
title = {Teleoperation of SCARA with Neural Network Based Controller},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {54},
number = {2},
year = {2008},
doi = {},
url = {https://www.sv-jme.eu/article/teleoperation-of-scara-with-neural-network-based-controller/}
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TY - JOUR AU - Čas, Jure AU - Klobučar, Rok AU - Hercog, Darko AU - Šafarič, Riko PY - 2017/11/03 TI - Teleoperation of SCARA with Neural Network Based Controller JF - Strojniški vestnik - Journal of Mechanical Engineering; Vol 54, No 2 (2008): Strojniški vestnik - Journal of Mechanical Engineering DO - KW - robotics, neutral network controller, remote experiment system, LabVIEW, MATLAB, Simulink, N2 - This paper describes the development of neural network based controller for the teleoperation of Selective Compliance Assembly Robot Arm (SCARA). The SCARA is controlled and teleoperated via the internet. Presented experiment isused by students at the University of Maribor as a remote educational tool. Application is based on MATLAB/Simulink and LabVIEW software packages. MATLAB/Simulink and developed library DSP-2 Library for Simulink are used for neural network control algorithm development, simulation and code generation. The executable code is downloaded to the Digital Signal Processor (DSP). The DSP controls through the analog and digital I/O the real process and maintain the data connection with the laboratory server. The LabVIEW virtual instrument(VI) is used as a client server application for the teleoperation. LabVIEW VI provides the ability for parameter tuning, signal monitoring, on-line analysis and via Remote Panels technology also teleoperation by using the internet browser (Internet Explorer). The main advantage of a neural network controller is the exploitation of its self-learning capability. For example: when friction or an unexpected disturbance occurs, the user of a remote application does not need any information about the changed robot dynamics, because it is estimated independently of the remote user. UR - https://www.sv-jme.eu/article/teleoperation-of-scara-with-neural-network-based-controller/
Čas, Jure, Klobučar, Rok, Hercog, Darko, AND Šafarič, Riko. "Teleoperation of SCARA with Neural Network Based Controller" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 54 Number 2 (03 November 2017)
Strojniški vestnik - Journal of Mechanical Engineering 54(2008)2, 94-102
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.
This paper describes the development of neural network based controller for the teleoperation of Selective Compliance Assembly Robot Arm (SCARA). The SCARA is controlled and teleoperated via the internet. Presented experiment isused by students at the University of Maribor as a remote educational tool. Application is based on MATLAB/Simulink and LabVIEW software packages. MATLAB/Simulink and developed library DSP-2 Library for Simulink are used for neural network control algorithm development, simulation and code generation. The executable code is downloaded to the Digital Signal Processor (DSP). The DSP controls through the analog and digital I/O the real process and maintain the data connection with the laboratory server. The LabVIEW virtual instrument(VI) is used as a client server application for the teleoperation. LabVIEW VI provides the ability for parameter tuning, signal monitoring, on-line analysis and via Remote Panels technology also teleoperation by using the internet browser (Internet Explorer). The main advantage of a neural network controller is the exploitation of its self-learning capability. For example: when friction or an unexpected disturbance occurs, the user of a remote application does not need any information about the changed robot dynamics, because it is estimated independently of the remote user.