Robotics: Science and Systems XXII
A Super-Resolution and Multi-Axis Tactile Sensor with Soft Artificial Skin
Hongxu Wei, Zhou Lu, Peisen Xu, Yang Xu, Xuanyi Yang, Wei Zhao, Jiming Chen, Gaofeng LiAbstract:
To achieve human-like skin tactile perception with super-resolution, the method of introducing a soft layer on sensing array has attracted increasing attention. Due to the limitations of sensing units principle, most existing tactile sensors can only sense normal force. However, multi-dimensional force information is important for robot manipulation. To address this, we propose a tactile sensing unit based on a tiny monolithic tri-cantilever structure that decouples three-dimensional force. A reconstruction algorithm combined both model-based and learning-based approaches is then proposed to detect the three-dimensional force applied to the sensing unit. These units are arranged in an array and covered with a soft silicone layer which induces traction-coupling effects. By leveraging deep learning, our tactile sensor can estimate the magnitude and position of external three-dimensional force with super-resolution. Experiments have shown that our tactile sensor achieves a Mean Absolute Error (MAE) of 0.19\,N for three-dimensional force estimation and 0.49\,mm for contact localization. Notably, this corresponds to a 26-fold improvement in spatial resolution, surpassing the state-of-the-art literature. Then the benefits and potential applications of our proposed sensors are validated in several tasks, including the teleoperative transfer of a test tube into a rack and stable robotic grasping under external interference. These demonstrate the practicality of our design and provide new solutions for tactile sensors.
Bibtex:
@INPROCEEDINGS{WeiH-RSS-26,
AUTHOR = {Hongxu Wei AND Zhou Lu AND Peisen Xu AND Yang Xu AND Xuanyi Yang AND Wei Zhao AND Jiming Chen AND Gaofeng Li},
TITLE = {{A Super-Resolution and Multi-Axis Tactile Sensor with Soft Artificial Skin}},
BOOKTITLE = {Proceedings of Robotics: Science and Systems},
YEAR = {2026},
ADDRESS = {Sydney, Australia},
MONTH = {July},
DOI = {10.15607/RSS.2026.XXII.199}
}
