TacShade A New 3D-printed Soft Optical Tactile Sensor Based on Light, Shadow and Greyscale for Shape Reconstruction

In this paper, we present the TacShade a newly designed 3D-printed soft optical tactile sensor. The sensor is developed for shape reconstruction under the inspiration of sketch drawing that uses the density of sketch lines to draw light and shadow, resulting in the creation of a 3D-view effect. TacShade, building upon the strengths of the TacTip, a single-camera tactile sensor of large in-depth deformation and being sensitive to edge and surface following, improves the structure in that the markers are distributed within the gap of papillae pins. Variations in light, dark, and grey effects can be generated inside the sensor through external contact interactions. The contours of the contacting objects are outlined by white markers, while the contact depth characteristics can be indirectly obtained from the distribution of black pins and white markers, creating a 2.5D visualization. Based on the imaging effect, we improve the Shape from Shading (SFS) algorithm to process tactile images, enabling a coarse but fast reconstruction for the contact objects. Two experiments are performed. The first verifies TacShade s ability to reconstruct the shape of the contact objects through one image for object distinction. The second experiment shows the shape reconstruction capability of TacShade for a large panel with ridged patterns based on the location of robots and image splicing technology.

ViTacTip: Design and Verification of a Novel Biomimetic Physical Vision-Tactile Fusion Sensor

Tactile sensing is significant for robotics since it can obtain physical contact information during manipulation. To capture multimodal contact information within a compact framework, we designed a novel sensor called ViTacTip, which seamlessly integrates both tactile and visual perception capabilities into a single, integrated sensor unit. ViTacTip features a transparent skin to capture fine features of objects during contact, which can be known as the see-through-skin mechanism. In the meantime, the biomimetic tips embedded in ViTacTip can amplify touch motions during tactile perception. For comparative analysis, we also fabricated a ViTac sensor devoid of biomimetic tips, as well as a TacTip sensor with opaque skin. Furthermore, we develop a Generative Adversarial Network (GAN)-based approach for modality switching between different perception modes, effectively alternating the emphasis between vision and tactile perception modes. We conducted a performance evaluation of the proposed sensor across three distinct tasks: i) grating identification, ii) pose regression, and iii) contact localization and force estimation. In the grating identification task, ViTacTip demonstrated an accuracy of 99.72%, surpassing TacTip, which achieved 94.60%. It also exhibited superior performance in both pose and force estimation tasks with the minimum error of 0.08mm and 0.03N, respectively, in contrast to ViTac's 0.12mm and 0.15N. Results indicate that ViTacTip outperforms single-modality sensors.