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 demonstrates 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.

翻译：由于人眼视网膜内解剖空间受限，视网膜手术需要极高的精度。为辅助外科医生达到此精度水平，具备灵巧操作能力的改进型集成机器人眼内蛇形臂（I2RIS）已被开发出来。然而，此类柔性腱驱动机器人常受迟滞问题困扰，这对精确控制与定位提出了重大挑战。特别是在小型I2RIS中，我们观察到了多阶段迟滞现象。本文提出一种扩展广义Prandtl-Ishlinskii（EGPI）模型以提高迟滞的拟合精度。该模型引入了一种新颖的切换机制，使其能够描述单调输入区域内的多阶段迟滞现象。基于I2RIS数据的实验验证表明，在多个电机输入方向上，EGPI模型在均方根误差、归一化均方根误差和平均绝对误差方面均优于传统广义Prandtl-Ishlinskii（GPI）模型。本研究中的EGPI模型凸显了其在微创柔性机器人多阶段迟滞建模中的应用潜力。