无透镜视觉触觉传感器，薄至10毫米，可实时感知接触信息
ThinTact:Thin Vision-Based Tactile Sensor by Lensless Imaging
- 用掩膜实现无透镜成像，将触碰映射为CMOS信号
- 提出基于DCT的快速重建算法，计算速度远超传统优化方法
- 适用于空间受限场景，如纹理识别和精细操作
基于视觉的触觉传感器在机器人领域日益受到关注。然而，传统透镜式设计对传感器厚度有最低限制，制约其在空间受限场景的应用。本文提出ThinTact，一种新型无透镜视觉触觉传感器，传感面积超过200 mm²，厚度小于10 mm。ThinTact采用掩膜式无透镜成像技术，将接触信息映射为CMOS信号。为实现实时触觉感知，提出一种基于离散余弦变换（DCT）的频域-空域联合滤波重建算法，计算效率显著高于现有优化方法。此外，开发了基于通用算法的掩膜优化方法及对应的系统矩阵校准算法，提升感知质量。通过定性与定量实验验证了无透镜重建与触觉感知性能。还展示了ThinTact在纹理识别和接触丰富物体操作等实际应用中的可行性。
原文摘要 · Abstract (English)
Vision-based tactile sensors have drawn increasing interest in the robotics community. However, traditional lens-based designs impose minimum thickness constraints on these sensors, limiting their applicability in space-restricted settings. In this paper, we propose ThinTact, a novel lensless vision-based tactile sensor with a sensing field of over 200 mm2 and a thickness of less than 10 mm.ThinTact utilizes the mask-based lensless imaging technique to map the contact information to CMOS signals. To ensure real-time tactile sensing, we propose a real-time lensless reconstruction algorithm that leverages a frequency-spatial-domain joint filter based on discrete cosine transform (DCT). This algorithm achieves computation significantly faster than existing optimization-based methods. Additionally, to improve the sensing quality, we develop a mask optimization method based on the generic algorithm and the corresponding system matrix calibration algorithm.We evaluate the performance of our proposed lensless reconstruction and tactile sensing through qualitative and quantitative experiments. Furthermore, we demonstrate ThinTact's practical applicability in diverse applications, including texture recognition and contact-rich object manipulation. The paper will appear in the IEEE Transactions on Robotics: https://ieeexplore.ieee.org/document/10842357. Video: https://youtu.be/YrOO9BDMAHo
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