# RainbowSight: A Family of Generalizable, Curved, Camera-Based Tactile Sensors For Shape Reconstruction

arXiv: https://arxiv.org/abs/2409.13649 · HTML: https://mlsanity.com/paper/2409.13649/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Sep 2024.

## Built on by (most cited first, 3 of 3)

- [NLiPsCalib: An Efficient Calibration Framework for High-Fidelity 3D Reconstruction of Curved Visuotactile Sensors](https://mlsanity.com/paper/2603.09319/) (2026)
- [Color-Encoded Illumination for High-Speed Volumetric Scene Reconstruction](https://mlsanity.com/paper/2604.26920/) (2026)
- [Calibration-Free Surface Normals Estimation in Vision-Based Tactile Sensing using Universal Photometric Stereo](https://mlsanity.com/paper/2609.31754/) (2026)

## Abstract (arXiv)

Camera-based tactile sensors can provide high resolution positional and local geometry information for robotic manipulation. Curved and rounded fingers are often advantageous, but it can be difficult to derive illumination systems that work well within curved geometries. To address this issue, we introduce RainbowSight, a family of curved, compact, camera-based tactile sensors which use addressable RGB LEDs illuminated in a novel rainbow spectrum pattern. In addition to being able to scale the illumination scheme to different sensor sizes and shapes to fit on a variety of end effector configurations, the sensors can be easily manufactured and require minimal optical tuning to obtain high resolution depth reconstructions of an object deforming the sensor's soft elastomer surface. Additionally, we show the advantages of our new hardware design and improvements in calibration methods for accurate depth map generation when compared to alternative lighting methods commonly implemented in previous camera-based tactile sensors. With these advancements, we make the integration of tactile sensors more accessible to roboticists by allowing them the flexibility to easily customize, fabricate, and calibrate camera-based tactile sensors to best fit the needs of their robotic systems.