This paper presents a contact-based 3-D surface measurement method based on a Digital Fringe Projection (DFP) system, belonging to the vision-based tactile sensing family pioneered by the commercially successful GelSight sensor. Such sensors have proven effective for robotic fingertip manipulation and contact sensing. However, because GelSight employs photometric stereo with RGB LEDs, it does not measure absolute depth directly but instead infers it by integrating estimated surface gradients, which can accumulate reconstruction errors; in addition, it becomes increasingly difficult to calibrate as the sensing area grows, and its depth accuracy is challenged on highly reflective or transparent objects. To overcome these drawbacks, we propose a fringe-projection-based contact measurement technique that performs triangulation-based 3-D reconstruction on a coated silicone contact surface, providing dense per-pixel surface geometry and full-field 3-D shape measurement over the contact region. By integrating high-accuracy digital fringe projection into the sensor, our approach simplifies calibration over larger areas and enhances depth precision for complex surfaces. Experimental results, including a direct comparison with a GelSight Mini sensor, a sphere-fitting accuracy evaluation, and an uncertainty analysis, confirm that the proposed method significantly improves the accuracy and stability of structured-light-based 3-D measurements, allowing reliable reconstruction of objects with diverse optical properties.

翻译：本文提出一种基于数字条纹投影（DFP）系统的接触式三维表面测量方法，属于商业成功的GelSight传感器开创的视觉触觉传感技术体系。此类传感器已被证实适用于机器人指尖操作与接触感知。然而，由于GelSight采用RGB LED光度立体视觉技术，其无法直接测量绝对深度，而是通过积分估算的表面梯度进行深度推断，这会导致重建误差累积；此外，随着传感面积增大，其校准难度显著增加，且对高反射或透明物体的深度测量精度存在局限。为克服上述缺陷，我们提出基于条纹投影的接触测量技术，在涂覆硅胶的接触表面执行三角测量三维重建，实现接触区域密集逐像素表面几何与全场三维形貌测量。通过将高精度数字条纹投影集成至传感器中，本方法简化了大面积校准过程，并提升了复杂表面的深度测量精度。实验验证包括与GelSight Mini传感器的直接对比、球面拟合精度评估及不确定度分析，结果表明所提方法显著提升了基于结构光的三维测量精度与稳定性，可实现对不同光学特性物体的可靠重建。