SymmeTac: 対称カラーLED駆動によるカメラベース触覚センサ向け高効率フォトメトリックスステレオ再構成法
SymmeTac: Symmetric Color LED Driven Efficient Photometric Stereo Reconstruction Methods for Camera-based Tactile Sensors
対称に配置した赤青LEDとCMOSチャンネル分離を利用し、2ショットで表面法線を推定する高効率なフォトメトリックスステレオ法を提案。演算を加算のみに最適化し、カメラベース触覚センサの高精度・高速な形状再構成を実現した。
著者: Jieji Ren, Heng Guo, Zaiyan Yang, Jinnuo Zhang, Yueshi Dong, Ningbin Zhang, Boxin Shi, Jiang Zou, Guoying Gu
分類: cs.RO
原文アブストラクト
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.
