用对称彩色LED实现高效高精度触觉传感器表面重建。
SymmeTac: Symmetric Color LED Driven Efficient Photometric Stereo Reconstruction Methods for Camera-based Tactile Sensors
- 通过红蓝光正交照射，两步完成四张图像采集。
- 表面法向估计准确，计算量大幅降低。
- 专为触觉传感器优化，纯加法运算提升效率。
基于摄像头的触觉传感器可在机器人与目标交互过程中提供高密度的表面几何和力信息。然而，现有方法难以在保证精度的同时实现高效重建，限制了其在机器人中的应用。为此，我们提出一种基于对称彩色LED分布的高效双光照光度立体方法。具体地，根据CMOS通道的感光响应曲线，设计正交的红光与蓝光作为照明光源，通过通道分离在两步内获取四张观测图。随后，构建双光照光度立体理论，可精确估计表面法向并显著降低计算开销。最后，结合摄像头触觉传感器特性，将算法优化为高度高效的纯加法运算。仿真与真实实验验证了该方法的优势。更多细节见：https://github.com/Tacxels/SymmeTac。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。