Camera-based tactile sensors can provide high-density surface geometry and force information for robots in the interaction process with the target. However, most existing methods cannot achieve accurate reconstruction with high efficiency, impeding the applications in robots. To address these problems, we propose an efficient two-shot photometric stereo method based on symmetric color LED distribution. Specifically, based on the sensing response curve of CMOS channels, we design orthogonal red and blue LEDs as illumination to acquire four observation maps using channel-splitting in a two-shot manner. Subsequently, we develop a two-shot photometric stereo theory, which can estimate accurate surface normal and greatly reduce the computing overhead in magnitude. Finally, leveraging the characteristics of the camera-based tactile sensor, we optimize the algorithm to be a highly efficient, pure addition operation. Simulation and real-world experiments demonstrate the advantages of our approach. Further details are available on: https://github.com/Tacxels/SymmeTac.

翻译：相机触觉传感器能够在机器人与目标交互过程中提供高密度的表面几何与力信息。然而，现有方法大多无法同时实现高精度与高效率的重建，限制了其在机器人领域的应用。为解决这些问题，我们提出一种基于对称彩色LED分布的高效双曝光光度立体方法。具体而言，基于CMOS通道的传感响应曲线，我们设计正交的红蓝LED作为照明光源，通过通道分离的双曝光方式获取四幅观测图。随后，我们发展了双曝光光度立体理论，该理论能够精确估计表面法向，并大幅降低计算开销。最后，结合相机触觉传感器的特性，我们将算法优化为一种高效、纯加法运算的实现方式。仿真与真实实验均验证了本方法的优势。更多细节请访问：https://github.com/Tacxels/SymmeTac。