Dynamic Characterization of a Parallel Haptic Device for Application as an Actuator in a Surgery Simulator

Abstract

Tactile sense is a key element in developing virtual reality simulators or surgical training systems. In this regard, haptic interfaces, the generator of a sense of touch, play a significant role in producing a realistic haptic feedback force. Since the majority of practical control theories are model-based, the identification of the robot dynamic model is a process of high importance and application. The main concern, accordingly, is to find a precise dynamic model for the aforementioned user interfaces. In this research, we have implemented the Lion identification method to characterize the dynamics of a parallel haptic device in actuating a surgery simulation. We chose the Novint Falcon as our haptic device which is a parallel impedance-type robot of low price, considerable load capacities, and proper workspace. In order to cover robot nonlinearities, we considered piecewise linear functions in different operational points in the robot workspace. With respect to the Lion Identification Method, we guaranteed the stability of error dynamic of estimations from the Lyapunov perspective. Thereafter, the dynamics of parameter estimation and the identification cost function are derived. Next by running a single-axis haptic experimental setup, the robot generated force is calibrated, and four different sets of sine wave inputs of various frequencies are imposed on the robot to calculate the required parameters by Matlab Simulink. The results reveal that the system parameters converge to the specific values while the output tracking error and its derivative behavior is reasonable, that is, the system identification is of great accuracy.