Recently, several morphologies, each with its advantages, have been proposed for the \textit{GelSight} high-resolution tactile sensors. However, existing simulation methods are limited to flat-surface sensors, which prevents their usage with the newer sensors of non-flat morphologies in Sim2Real experiments. In this paper, we extend a previously proposed GelSight simulation method developed for flat-surface sensors and propose a novel method for curved sensors. In particular, we address the simulation of light rays travelling through a curved tactile membrane in the form of geodesic paths. The method is validated by simulating the finger-shaped GelTip sensor and comparing the generated synthetic tactile images against the corresponding real images. Our extensive experiments show that combining the illumination generated from the geodesic paths, with a background image from the real sensor, produces the best results when compared to the lighting generated by direct linear paths in the same conditions. As the method is parameterised by the sensor mesh, it can be applied in principle to simulate a tactile sensor of any morphology. The proposed method not only unlocks simulating existing optical tactile sensors of complex morphologies but also enables experimenting with sensors of novel morphologies, before the fabrication of the real sensor. Project website: https://danfergo.github.io/geltip-sim

翻译：摘要：近年来，针对\textit{GelSight}高分辨率触觉传感器已提出了多种各有优势的形态设计方案。然而，现有仿真方法仅局限于平面传感器，这阻碍了其在Sim2Real实验中应用于具有非平面形态的新型传感器。本文对先前针对平面传感器提出的GelSight仿真方法进行扩展，提出了一种面向曲面传感器的新方法。具体而言，我们通过测地线路径模拟了光线在曲面触觉膜中的传播过程。通过仿真指形GelTip传感器并将生成的合成触觉图像与对应真实图像进行对比，验证了该方法的有效性。大量实验表明，在相同条件下，相较于基于直接线性路径生成的光照，结合测地线路径生成的光照与真实传感器背景图像的方法可获得最优结果。由于该方法以传感器网格为参数化依据，理论上可适用于任意形态触觉传感器的仿真。该方案不仅突破了对现有复杂形态光学触觉传感器的仿真限制，更使得在实际传感器制造前即可对新型形态传感器进行实验探索。项目网站：https://danfergo.github.io/geltip-sim