Modeling, characterization and control of antagonistic SMA springs for use in a neurosurgical robot

In this paper, we model and characterize the thermomechanical behavior of SMA springs based on Brinson's constitutive model of SMAs. The model developed in this paper can be used to compute the recovery length of SMA springs. We used the model to develop a temperature feedback position controller to control the joint motion of the SMA spring-actuated robot. We also implemented a position controller for the robot using image feedback because the robot was designed to be operated under MRI guidance. Since the image tracking algorithm for image feedback control may fail in some situations, the temperature feedback controller can be used as a backup control scheme for the robot. The experimental results showed that the image feedback controller worked well while the temperature feedback controller did not. This is because the theoretical model did not include the nonlinear characteristics of the tendon-sheath mechanisms. Therefore, we used an empirical model to implement a temperature feedback controller and it was used to control the robot precisely.

[1]  Yoshihiko Nakamura,et al.  Shape-memory-alloy active forceps for laparoscopic surgery , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[2]  K. Tanaka.  A THERMOMECHANICAL SKETCH OF SHAPE MEMORY EFFECT: ONE-DIMENSIONAL TENSILE BEHAVIOR , 1986 .

[3]  Joseph Edward Shigley,et al.  Mechanical engineering design , 1972 .

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

[5]  L. Brinson.  One-Dimensional Constitutive Behavior of Shape Memory Alloys: Thermomechanical Derivation with Non-Constant Material Functions and Redefined Martensite Internal Variable , 1993 .

[6]  Jaydev P. Desai,et al.  Towards a MR image-guided SMA-actuated neurosurgical robot , 2011, 2011 IEEE International Conference on Robotics and Automation.

[7]  Gangbing Song,et al.  Position control of shape memory alloy actuators with internal electrical resistance feedback using neural networks , 2004 .

[8]  Jaydev P. Desai,et al.  Toward a Meso-Scale SMA-Actuated MRI-Compatible Neurosurgical Robot , 2012, IEEE Transactions on Robotics.

[9]  Craig A. Rogers,et al.  One-Dimensional Thermomechanical Constitutive Relations for Shape Memory Materials , 1990 .

[10]  Edward J. Park,et al.  A shape memory alloy-based tendon-driven actuation system for biomimetic artificial fingers, part I: design and evaluation , 2009, Robotica.

[11]  C. Liang,et al.  Design of Shape Memory Alloy Springs with Applications in Vibration Control , 1997 .

[12]  Roy Featherstone,et al.  An Architecture for Fast and Accurate Control of Shape Memory Alloy Actuators , 2008, Int. J. Robotics Res..

[13]  Bin Yao,et al.  Modeling of Transmission Characteristics Across a Cable-Conduit System , 2010, IEEE Transactions on Robotics.

[14]  Koji Ikuta,et al.  Shape memory alloy servo actuator system with electric resistance feedback and application for active endoscope , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[15]  Yu Chen,et al.  Towards a discretely actuated steerable cannula for diagnostic and therapeutic procedures , 2012, Int. J. Robotics Res..

[16]  Andreas Anayiotos,et al.  Comparative MRI compatibility of 316 L stainless steel alloy and nickel-titanium alloy stents. , 2002, Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance.

[17]  Jaydev P. Desai,et al.  Towards the development of a SMA-actuated MRI-compatible tendon-driven neurosurgical robot , 2012, 2012 IEEE International Conference on Robotics and Automation.

[18]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[19]  J. Engh,et al.  Endoscopic Port Surgery for Intraparenchymal Brain Tumors , 2011 .