HySenSe: A Hyper-Sensitive and High-Fidelity Vision-Based Tactile Sensor
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Abstract (arXiv)
In this paper, to address the sensitivity and durability trade-off of Vision-based Tactile Sensor (VTSs), we introduce a hyper-sensitive and high-fidelity VTS called HySenSe. We demonstrate that by solely changing one step during the fabrication of the gel layer of the GelSight sensor (as the most well-known VTS), we can substantially improve its sensitivity and durability. Our experimental results clearly demonstrate the outperformance of the HySenSe compared with a similar GelSight sensor in detecting textural details of various objects under identical experimental conditions and low interaction forces (<= 1.5 N).
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Nov 2022.
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Citing papers per year: 2022: 1; 2023: 2; 2024: 1.
4 papers.
- 2023Towards Reliable Colorectal Cancer Polyps Classification via Vision Based Tactile Sensing and Confidence-Calibrated Neural Networkscited by 2
- 2022Pit-Pattern Classification of Colorectal Cancer Polyps Using a Hyper Sensitive Vision-Based Tactile Sensor and Dilated Residual Networkscited by 1
- 2023Towards Design and Development of an ArUco Markers-Based Quantitative Surface Tactile Sensorcited by 0
- 2024Robot-Enabled Machine Learning-Based Diagnosis of Gastric Cancer Polyps Using Partial Surface Tactile Imagingcited by 0
- 2024Robot-Enabled Machine Learning-Based Diagnosis of Gastric Cancer Polyps Using Partial Surface Tactile Imaging2 Aug 2024
- 2023Towards Design and Development of an ArUco Markers-Based Quantitative Surface Tactile Sensor12 Oct 2023
- 2023Towards Reliable Colorectal Cancer Polyps Classification via Vision Based Tactile Sensing and Confidence-Calibrated Neural Networks25 Apr 2023
- 2022Pit-Pattern Classification of Colorectal Cancer Polyps Using a Hyper Sensitive Vision-Based Tactile Sensor and Dilated Residual Networks13 Nov 2022