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Recently, several morphologies, each with its advantages, have been proposedfor the \textit{GelSight} high-resolution tactile sensors. However, existingsimulation methods are limited to flat-surface sensors, which prevents theirusage with the newer sensors of non-flat morphologies in Sim2Real experiments.In this paper, we extend a previously proposed GelSight simulation methoddeveloped for flat-surface sensors and propose a novel method for curvedsensors. In particular, we address the simulation of light rays travellingthrough a curved tactile membrane in the form of geodesic paths. The method isvalidated by simulating the finger-shaped GelTip sensor and comparing thegenerated synthetic tactile images against the corresponding real images. Ourextensive experiments show that combining the illumination generated from thegeodesic paths, with a background image from the real sensor, produces the bestresults when compared to the lighting generated by direct linear paths in thesame conditions. As the method is parameterised by the sensor mesh, it can beapplied in principle to simulate a tactile sensor of any morphology. Theproposed method not only unlocks simulating existing optical tactile sensors ofcomplex morphologies but also enables experimenting with sensors of novelmorphologies, before the fabrication of the real sensor. Project website:https://danfergo.github.io/geltip-sim

Beyond Flat GelSight Sensors: Simulation of Optical Tactile Sensors of Complex Morphologies for Sim2Real Learning