An Extended Generalized Prandtl-Ishlinskii Hysteresis Model for I2RIS Robot

TL;DR

This study addresses the challenge of multi-stage hysteresis in the tendon-driven I2RIS robotic system used for retinal microsurgery. It introduces an Extended Generalized Prandtl–Ishlinskii (EGPI) model with a switching mechanism between multiple GPI components to capture complex hysteresis behavior in monotonic input regions. Experimental and simulation results demonstrate that EGPI significantly outperforms the conventional GPI in RMSE, NRMSE, and MAE across yaw and pitch motions, highlighting its potential for improved precision control in minimally invasive flexible robots. The findings suggest that EGPI can be extended to other hysteretic actuation scenarios and may pave the way for analytical inverse formulations and compensation strategies in robotic microsurgery.

Abstract

Retinal surgery requires extreme precision due to constrained anatomical spaces in the human retina. To assist surgeons achieve this level of accuracy, the Improved Integrated Robotic Intraocular Snake (I2RIS) with dexterous capability has been developed. However, such flexible tendon-driven robots often suffer from hysteresis problems, which significantly challenges precise control and positioning. In particular, we observed multi-stage hysteresis phenomena in the small-scale I2RIS. In this paper, we propose an Extended Generalized Prandtl-Ishlinskii (EGPI) model to increase the fitting accuracy of the hysteresis. The model incorporates a novel switching mechanism that enables it to describe multi-stage hysteresis in the regions of monotonic input. Experimental validation on I2RIS data demonstrate that the EGPI model outperforms the conventional Generalized Prandtl-Ishlinskii (GPI) model in terms of RMSE, NRMSE, and MAE across multiple motor input directions. The EGPI model in our study highlights the potential in modeling multi-stage hysteresis in minimally invasive flexible robots.

Figures (6)

• Figure 1: The I$^2$RIS attached to the SHER 3.0 handle.
• Figure 2: Experimental setup.
• Figure 3: (a) An example of I2RIS data with multi-stage hysteresis $S_1$,$S_2$ and $S_3$: Absolute yaw bending angle as a function of absolute yaw motor encoder value. (b) An example of the GPI operator. (c) Output of the GPI model $z_1$. (d) Output of the GPI model $z_2$.
• Figure 4: Output of the EGPI model.
• Figure 5: Input encoder value of each motors. (a) Input greater than zero. (b) Input less than zero.