Nonlinear modeling and parameter identification of dynamic friction model in tendon sheath for flexible endoscopic systems

Minimally Invasive Surgery (MIS) has established a revolution in surgical communities, with its many advantages over open surgery. The need of more simplicity and high maneuverability makes the tendon sheath a very suitable mechanism in flexible endoscopic systems. Due to...

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Bibliographic Details
Main Authors: Thanh Nho, Do, Tjahjowidodo, Tegoeh, Lau, Michael Wai Shing, Phee, Soo Jay
Other Authors: School of Mechanical and Aerospace Engineering
Format: Conference or Workshop Item
Language:English
Published: 2014
Subjects:
Online Access:https://hdl.handle.net/10356/105802
http://hdl.handle.net/10220/20900
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Institution: Nanyang Technological University
Language: English
Description
Summary:Minimally Invasive Surgery (MIS) has established a revolution in surgical communities, with its many advantages over open surgery. The need of more simplicity and high maneuverability makes the tendon sheath a very suitable mechanism in flexible endoscopic systems. Due to the restriction on size constraints and sterilization problems, traditional sensors cannot be mounted on the tool tips of a slave manipulator. Moreover, in the presence of nonlinear friction and hysteresis between the tendon and the sheath, it is extremely difficult to control the precise motion and sense the force during the operation. This paper proposes a new dynamic friction model to estimate the force at the end effector for the tendon sheath mechanism. The proposed friction model can adapt with any initial pretension of the tendon and any configuration of the sheath. The nonlinearities in both sliding and presliding regimes can be captured by using an internal state variable and functions dependent velocity and acceleration. A specific setup has been designed in order to measure the friction force between the tendon and the sheath. Finally, the validity of the identified model is confirmed by a good agreement of its prediction and experimental data.