针对微创柔性机器人多阶段滞回问题，提出改进的普兰特尔-伊斯林斯基模型
An Extended Generalized Prandtl-Ishlinskii Hysteresis Model for I2RIS Robot
- 引入切换机制，提升多阶段滞回建模精度
- 在多个输入方向上，误差指标均优于传统模型
- 适用于高精度医疗机器人控制，尤其适合微创手术
视网膜手术因人体眼内空间受限，要求极高操作精度。为辅助医生实现这一目标，已开发出具备灵巧操控能力的改进型集成式机器人眼内蛇形系统（I2RIS）。然而，此类柔性缆绳驱动机器人常面临滞回问题，严重影响精确控制与定位。特别是小型I2RIS表现出多阶段滞回现象。本文提出扩展广义普兰特尔-伊斯林斯基（EGPI）模型，以提高滞回拟合精度。该模型引入新型切换机制，可有效描述单调输入区域内的多阶段滞回特性。基于I2RIS实测数据的实验验证表明，与传统广义普兰特尔-伊斯林斯基（GPI）模型相比，EGPI模型在多个电机输入方向上，均显著降低均方根误差（RMSE）、归一化均方根误差（NRMSE）和平均绝对误差（MAE）。本研究结果展示了该模型在微创柔性机器人多阶段滞回建模中的潜力。
原文摘要 · Abstract (English)
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.
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