State Key Lab of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
Sensors (Basel). 2022 Aug 28;22(17):6470. doi: 10.3390/s22176470.
Tactile sensing plays an important role for robots' perception, but the existing tactile technologies have multiple limitations. Visual-tactile sensor (VTS) is a newly developed tactile detector; it perceives the contacting surface shape, or even more refined texture, by way of the contact deformation image captured by a camera. A conventional visual perception is usually formulated as a data processing. It suffers issues of cumbersome training set and complicated calibration procedures. A novel model-based depth perceptual scheme is proposed where a mapping from the image intensity to the contact geometry is mathematically formulated with an associated tailored fast solver. The hardware calibration requires single image only, leading to an outstanding algorithmic robustness. The non-uniformity of the illumination condition is embodied by the stereo model, resulting in a robust depth perception precision. Compression tests on a prototype VTS showed the method's capability in high-quality geometry reconstruction. Both contacting shape and texture were captured at a root-mean-square error down to a sub-millimeter level. The feasibility of the proposed in a pose estimation application is further experimentally validated. The associated tests yielded estimation errors that were all less than 3° in terms of spatial orientation and all less than 1mm in terms of translation.
触觉在机器人感知中起着重要作用,但现有的触觉技术存在多种局限性。视觉触觉传感器(VTS)是一种新开发的触觉探测器;它通过相机捕捉到的接触变形图像来感知接触表面的形状,甚至更精细的纹理。传统的视觉感知通常被表述为数据处理。它存在训练集繁琐和校准过程复杂的问题。本文提出了一种基于模型的深度感知方案,其中从图像强度到接触几何形状的映射通过一个相关的定制快速求解器进行数学公式化。硬件校准只需要单张图像,从而具有出色的算法鲁棒性。光照条件的不均匀性通过立体模型体现,从而实现了稳健的深度感知精度。对原型 VTS 的压缩测试显示了该方法在高质量几何重建方面的能力。接触形状和纹理都以均方根误差低至亚毫米级别的方式被捕捉到。进一步通过实验验证了所提出方法在姿态估计应用中的可行性。相关测试的结果表明,在空间方向上的估计误差均小于 3°,在平移方向上的估计误差均小于 1mm。