Neural Network Enhanced Robot Tool Identification and Calibration for Bilateral Teleoperation
In teleoperated surgery, the transmission of force feedback from the remote environment to the surgeon at the local site requires the availability of reliable force information in the system. In general, a force sensor is mounted between the slave end-effector and the tool for measuring the interact...
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doaj-1e43a63a4bab47deaaac4b2992b5f2d82021-03-29T23:15:29ZengIEEEIEEE Access2169-35362019-01-01712204112205110.1109/ACCESS.2019.29363348805341Neural Network Enhanced Robot Tool Identification and Calibration for Bilateral TeleoperationHang Su0Chenguang Yang1https://orcid.org/0000-0001-5255-5559Hussein Mdeihly2Alessandro Rizzo3Giancarlo Ferrigno4Elena De Momi5Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, ItalyBristol Robotics Laboratory, University of the West of England, Bristol, U.K.Department of Electronics and Telecommunications, Politecnico di Torino, Torino, ItalyDepartment of Electronics and Telecommunications, Politecnico di Torino, Torino, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, ItalyIn teleoperated surgery, the transmission of force feedback from the remote environment to the surgeon at the local site requires the availability of reliable force information in the system. In general, a force sensor is mounted between the slave end-effector and the tool for measuring the interaction forces generated at the remote sites. Such as the acquired force value includes not only the interaction force but also the tool gravity. This paper presents a neural network (NN) enhanced robot tool identification and calibration for bilateral teleoperation. The goal of this experimental study is to implement and validate two different techniques for tool gravity identification using Curve Fitting (CF) and Artificial Neural Networks (ANNs), separately. After tool identification, calibration of multi-axis force sensor based on Singular Value Decomposition (SVD) approach is introduced for alignment of the forces acquired from the force sensor and acquired from the robot. Finally, a bilateral teleoperation experiment is demonstrated using a serial robot (LWR4+, KUKA, Germany) and a haptic manipulator (SIGMA 7, Force Dimension, Switzerland). Results demonstrated that the calibration of the force sensor after identifying tool gravity component by using ANN shows promising performance than using CF. Additionally, the transparency of the system was demonstrated using the force and position tracking between the master and slave manipulators.https://ieeexplore.ieee.org/document/8805341/Artificial neural networkbilateral teleoperationcalibrationtool identification |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hang Su Chenguang Yang Hussein Mdeihly Alessandro Rizzo Giancarlo Ferrigno Elena De Momi |
spellingShingle |
Hang Su Chenguang Yang Hussein Mdeihly Alessandro Rizzo Giancarlo Ferrigno Elena De Momi Neural Network Enhanced Robot Tool Identification and Calibration for Bilateral Teleoperation IEEE Access Artificial neural network bilateral teleoperation calibration tool identification |
author_facet |
Hang Su Chenguang Yang Hussein Mdeihly Alessandro Rizzo Giancarlo Ferrigno Elena De Momi |
author_sort |
Hang Su |
title |
Neural Network Enhanced Robot Tool Identification and Calibration for Bilateral Teleoperation |
title_short |
Neural Network Enhanced Robot Tool Identification and Calibration for Bilateral Teleoperation |
title_full |
Neural Network Enhanced Robot Tool Identification and Calibration for Bilateral Teleoperation |
title_fullStr |
Neural Network Enhanced Robot Tool Identification and Calibration for Bilateral Teleoperation |
title_full_unstemmed |
Neural Network Enhanced Robot Tool Identification and Calibration for Bilateral Teleoperation |
title_sort |
neural network enhanced robot tool identification and calibration for bilateral teleoperation |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2019-01-01 |
description |
In teleoperated surgery, the transmission of force feedback from the remote environment to the surgeon at the local site requires the availability of reliable force information in the system. In general, a force sensor is mounted between the slave end-effector and the tool for measuring the interaction forces generated at the remote sites. Such as the acquired force value includes not only the interaction force but also the tool gravity. This paper presents a neural network (NN) enhanced robot tool identification and calibration for bilateral teleoperation. The goal of this experimental study is to implement and validate two different techniques for tool gravity identification using Curve Fitting (CF) and Artificial Neural Networks (ANNs), separately. After tool identification, calibration of multi-axis force sensor based on Singular Value Decomposition (SVD) approach is introduced for alignment of the forces acquired from the force sensor and acquired from the robot. Finally, a bilateral teleoperation experiment is demonstrated using a serial robot (LWR4+, KUKA, Germany) and a haptic manipulator (SIGMA 7, Force Dimension, Switzerland). Results demonstrated that the calibration of the force sensor after identifying tool gravity component by using ANN shows promising performance than using CF. Additionally, the transparency of the system was demonstrated using the force and position tracking between the master and slave manipulators. |
topic |
Artificial neural network bilateral teleoperation calibration tool identification |
url |
https://ieeexplore.ieee.org/document/8805341/ |
work_keys_str_mv |
AT hangsu neuralnetworkenhancedrobottoolidentificationandcalibrationforbilateralteleoperation AT chenguangyang neuralnetworkenhancedrobottoolidentificationandcalibrationforbilateralteleoperation AT husseinmdeihly neuralnetworkenhancedrobottoolidentificationandcalibrationforbilateralteleoperation AT alessandrorizzo neuralnetworkenhancedrobottoolidentificationandcalibrationforbilateralteleoperation AT giancarloferrigno neuralnetworkenhancedrobottoolidentificationandcalibrationforbilateralteleoperation AT elenademomi neuralnetworkenhancedrobottoolidentificationandcalibrationforbilateralteleoperation |
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