Robotics technology is used widely in minimally invasive surgery (MIS) which provides high performance and accuracy. The most famous robot arm mechanisms, which are used in MIS, are tendon-driven mechanism (TDM), and concentric tube mechanism (CTM). Unfortunately, these mechanisms until now have some limitations, i.e. making friction with the tissue during extracting and retracting and strain limits, for TDM and CTM respectively. A new hybrid concentric tube-tendon driven mechanism (HCTDM) is proposed to overcome these limitations. HCTDM enables the end-effector to get close to and get away from the surgical area during the operation without harming the tissue and with more flexibility. In addition to that, the workspace increases as a result of this combination, too. This benefit serves MIS, especially endoscopic surgeries (ESs). We did an analytical study of this idea and got the forward kinematics. In the inverse kinematics, an intelligent approach which is called an adaptive neuro-fuzzy inference system (ANFIS) is used because the closed-form solution is more complicated for such these mechanisms. Finally, HCTDM is analyzed and evaluated by using a computer simulation. The simulation results show that the workspace becomes wider and has more dexterity than use TDM or CTM individually. Furthermore, various trajectories are used to test the mechanism and the kinematic analysis, which show the mechanism can follow and track the trajectories with maximum mean error 1.279, 0.7027, and [Formula: see text] for X, Y, and Z axes respectively.
High-Performance Adaptive Neurofuzzy Classifier with a Parametric Tuning
