Deep learning for haptic feedback of flexible endoscopic robot without prior knowledge on sheath configuration

[1]  D. Ruelle,et al.  Recurrence Plots of Dynamical Systems , 1987 .

[2]  Kazuo Tanie,et al.  A new consideration on tendon-tension control system of robot hands , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[3]  M. Koebbe Use of recurrence plots in analysis of time-series data , 1992 .

[4]  J. Bokor,et al.  Bragg gratings fabricated in monomode photosensitive optical fiber by UV exposure through a phase mask , 1993 .

[5]  Robert D. Howe,et al.  Remote palpation technology , 1995 .

[6]  W Herzog,et al.  Dynamic muscle force predictions from EMG: an artificial neural network approach. , 1999, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[7]  B. Hannaford,et al.  Force controlled and teleoperated endoscopic grasper for minimally invasive surgery-experimental performance evaluation , 1999, IEEE Transactions on Biomedical Engineering.

[8]  Lin Wang,et al.  Prediction of joint moments using a neural network model of muscle activations from EMG signals , 2002, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[9]  M. Ausloos,et al.  RECURRENCE PLOT AND RECURRENCE QUANTIFICATION ANALYSIS TECHNIQUES FOR DETECTING A CRITICAL REGIME. EXAMPLES FROM FINANCIAL MARKET INIDICES , 2004, cond-mat/0412765.

[10]  Jaydev P. Desai,et al.  Design, Development, and Testing of an Automated Laparoscopic Grasper with 3-D Force Measurement Capability , 2004, ISMS.

[11]  Masakatsu G. Fujie,et al.  Integration of a Miniaturised Triaxial Force Sensor in a Minimally Invasive Surgical Tool , 2006, IEEE Transactions on Biomedical Engineering.

[12]  Gianluca Palli,et al.  OPTIMAL CONTROL OF TENDON-SHEATH TRANSMISSION SYSTEMS , 2006 .

[13]  Gianluca Palli,et al.  Model and control of tendon-sheath transmission systems , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[14]  B. Yao,et al.  Modeling of a closed loop cable-conduit transmission system , 2008, 2008 IEEE International Conference on Robotics and Automation.

[15]  S. J. Phee,et al.  Master and slave transluminal endoscopic robot (MASTER) for natural Orifice Transluminal Endoscopic Surgery (NOTES) , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[16]  A. Okamura Haptic feedback in robot-assisted minimally invasive surgery , 2009, Current opinion in urology.

[17]  Paolo Dario,et al.  Tendon sheath analysis for estimation of distal end force and elongation , 2009, 2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

[18]  Kotaro Tadano,et al.  Development of a Master–Slave System with Force-Sensing Abilities using Pneumatic Actuators for Laparoscopic Surgery , 2010, Adv. Robotics.

[19]  Gregory D. Hager,et al.  Motion generation of robotic surgical tasks: Learning from expert demonstrations , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[20]  Gianluca Palli,et al.  Modeling, Identification, and Control of Tendon-Based Actuation Systems , 2012, IEEE Transactions on Robotics.

[21]  S. Phee,et al.  Robot-assisted endoscopic submucosal dissection is effective in treating patients with early-stage gastric neoplasia. , 2012, Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association.

[22]  Tegoeh Tjahjowidodo,et al.  Nonlinear Modeling and Parameter Identification of Dynamic Friction Model in Tendon Sheath for Flexible Endoscopic Systems , 2013, ICINCO.

[23]  Soo Jay Phee,et al.  Haptic feedback and control of a flexible surgical endoscopic robot , 2013, Comput. Methods Programs Biomed..

[24]  Christopher Potts,et al.  Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank , 2013, EMNLP.

[25]  Chee-Meng Chew,et al.  Muscle force estimation with surface EMG during dynamic muscle contractions: A wavelet and ANN based approach , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[26]  Corneliu Rablau,et al.  Providing haptic feedback in robot-assisted minimally invasive surgery: A direct optical force-sensing solution for haptic rendering of deformable bodies , 2013, Computer aided surgery : official journal of the International Society for Computer Aided Surgery.

[27]  Tegoeh Tjahjowidodo,et al.  Hysteresis modeling and position control of tendon-sheath mechanism in flexible endoscopic systems , 2014 .

[28]  Tegoeh Tjahjowidodo,et al.  An investigation of friction-based tendon sheath model appropriate for control purposes , 2014 .

[29]  J. Balic,et al.  Prediction of Cutting Forces with Neural Network by Milling Functionally Graded Material , 2014 .

[30]  Quoc V. Le,et al.  Sequence to Sequence Learning with Neural Networks , 2014, NIPS.

[31]  Soo Jay Phee,et al.  Modeling and motion compensation of a bidirectional tendon-sheath actuated system for robotic endoscopic surgery , 2015, Comput. Methods Programs Biomed..

[32]  Danail Stoyanov,et al.  Surgical robotics beyond enhanced dexterity instrumentation: a survey of machine learning techniques and their role in intelligent and autonomous surgical actions , 2016, International Journal of Computer Assisted Radiology and Surgery.

[33]  A. Krakovská,et al.  Use of False Nearest Neighbours for Selecting Variables and Embedding Parameters for State Space Reconstruction , 2015 .

[34]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[35]  David Silver,et al.  Memory-based control with recurrent neural networks , 2015, ArXiv.

[36]  Brian Byunghyun Kang,et al.  Feasibility study of a slack enabling actuator for actuating tendon-driven soft wearable robot without pretension , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[37]  Tegoeh Tjahjowidodo,et al.  A new approach of friction model for tendon-sheath actuated surgical systems: Nonlinear modelling and parameter identification , 2015 .

[38]  Tegoeh Tjahjowidodo,et al.  Nonlinear friction modelling and compensation control of hysteresis phenomena for a pair of tendon-sheath actuated surgical robots , 2015 .

[39]  Jurandy Almeida,et al.  Fusion of time series representations for plant recognition in phenology studies , 2016, Pattern Recognit. Lett..

[40]  Hoo-Chang Hoo-Chang Shin Shin,et al.  Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning , 2016, Ieee Transactions on Medical Imaging.

[41]  Hongliang Ren,et al.  Data‐driven methods towards learning the highly nonlinear inverse kinematics of tendon‐driven surgical manipulators , 2017, The international journal of medical robotics + computer assisted surgery : MRCAS.

[42]  Lin Cao,et al.  Towards active variable stiffness manipulators for surgical robots , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).

[43]  Beth Jelfs,et al.  Self-Recalibrating Surface EMG Pattern Recognition for Neuroprosthesis Control Based on Convolutional Neural Network , 2017, Front. Neurosci..

[44]  Xuefang Li,et al.  Adaptive Boundary Iterative Learning Control for an Euler–Bernoulli Beam System With Input Constraint , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[45]  Sergio Escalera,et al.  Beyond One-hot Encoding: lower dimensional target embedding , 2018, Image Vis. Comput..

[46]  Zhilin Xu,et al.  Distal End Force Sensing with Optical Fiber Bragg Gratings for Tendon-Sheath Mechanisms in Flexible Endoscopic Robots , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

[47]  Feifei Ren,et al.  The Temperature Compensation of FBG Sensor for Monitoring the Stress on Hole-Edge , 2018, IEEE Photonics Journal.

[48]  Wei He,et al.  Adaptive Fuzzy Neural Network Control for a Constrained Robot Using Impedance Learning , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[49]  Stefan Wermter,et al.  Speeding up the Hyperparameter Optimization of Deep Convolutional Neural Networks , 2018, Int. J. Comput. Intell. Appl..

[50]  Robert X. Gao,et al.  Deep learning and its applications to machine health monitoring , 2019, Mechanical Systems and Signal Processing.

[51]  Lin Cao,et al.  A Novel Robotic Suturing System for Flexible Endoscopic Surgery , 2019, 2019 International Conference on Robotics and Automation (ICRA).

[52]  Wei He,et al.  PDE Model-Based Boundary Control Design for a Flexible Robotic Manipulator With Input Backlash , 2019, IEEE Transactions on Control Systems Technology.

[53]  Lin Cao,et al.  Distal-end force prediction of tendon-sheath mechanisms for flexible endoscopic surgical robots using deep learning , 2019, Mechanism and Machine Theory.

[54]  Lin Cao,et al.  A Novel Methodology for Comprehensive Modeling of the Kinetic Behavior of Steerable Catheters , 2019, IEEE/ASME Transactions on Mechatronics.

[55]  Lin Cao,et al.  Pneumatically Actuated Deployable Tissue Distension Device for NOTES for Colon , 2019, 2019 International Conference on Robotics and Automation (ICRA).