Comparing Piezoresistive Substrates for Tactile Sensing in Dexterous Hands
This work addresses the need for scalable tactile skins in dexterous robotic hands, though it is incremental as it builds on existing piezoresistive sensing methods.
The paper tackled the problem of improving tactile sensing for robotic grasping by proposing a novel sensor design using piezoresistive materials, finding that anti-static foam performs comparably to specialized fabrics in benchtop experiments and demonstrating its use in contact detection and localization during manipulation tasks.
While tactile skins have been shown to be useful for detecting collisions between a robotic arm and its environment, they have not been extensively used for improving robotic grasping and in-hand manipulation. We propose a novel sensor design for use in covering existing multi-fingered robot hands. We analyze the performance of four different piezoresistive materials using both fabric and anti-static foam substrates in benchtop experiments. We find that although the piezoresistive foam was designed as packing material and not for use as a sensing substrate, it performs comparably with fabrics specifically designed for this purpose. While these results demonstrate the potential of piezoresistive foams for tactile sensing applications, they do not fully characterize the efficacy of these sensors for use in robot manipulation. As such, we use a low density foam substrate to develop a scalable tactile skin that can be attached to the palm of a robotic hand. We demonstrate several robotic manipulation tasks using this sensor to show its ability to reliably detect and localize contact, as well as analyze contact patterns during grasping and transport tasks. Our project website provides details on all materials, software, and data used in the sensor development and analysis: https://sites.google.com/gcloud.utah.edu/piezoresistive-tactile-sensing/.