DelTact: A Vision-based Tactile Sensor Using Dense Color Pattern

Tactile sensing is an essential perception for robots to complete dexterous tasks. As a promising tactile sensing technique, vision-based tactile sensors have been developed to improve robot manipulation performance. Here we propose a new design of our vision-based tactile sensor, DelTact, with its high-resolution sensing abilities of multiple modality surface contact information. The sensor adopts an improved dense random color pattern based on previous version, using a modular hardware architecture to achieve higher accuracy of contact deformation tracking whilst at the same time maintaining a compact and robust overall design. In particular, we optimized the color pattern generation process and selected the appropriate pattern for coordinating with a dense optical flow in a real-world experimental sensory setting using varied contact objects. A dense tactile flow was obtained from the raw image in order to determine shape and force distribution on the contact surface. This sensor can be easily integrated with a parallel gripper where experimental results using qualitative and quantitative analysis demonstrated that the sensor is capable of providing tactile measurements with high temporal and spatial resolution.