ThinTact:Thin Vision-Based Tactile Sensor by Lensless Imaging
Jing Xu, Weihang Chen, Hongyu Qian, Dan Wu, Rui Chen

TL;DR
ThinTact introduces a compact, lensless vision-based tactile sensor with real-time reconstruction capabilities, enabling effective tactile sensing in space-constrained robotics applications.
Contribution
The paper presents a novel lensless tactile sensor design, a fast DCT-based reconstruction algorithm, and a mask optimization method, advancing tactile sensing technology in size and speed.
Findings
Achieves over 200 mm2 sensing area with less than 10 mm thickness.
Provides real-time tactile reconstruction significantly faster than existing methods.
Demonstrates effective texture recognition and object manipulation applications.
Abstract
Vision-based tactile sensors have drawn increasing interest in the robotics community. However, traditional lens-based designs impose minimum thickness constraints on these sensors, limiting their applicability in space-restricted settings. In this paper, we propose ThinTact, a novel lensless vision-based tactile sensor with a sensing field of over 200 mm2 and a thickness of less than 10 mm.ThinTact utilizes the mask-based lensless imaging technique to map the contact information to CMOS signals. To ensure real-time tactile sensing, we propose a real-time lensless reconstruction algorithm that leverages a frequency-spatial-domain joint filter based on discrete cosine transform (DCT). This algorithm achieves computation significantly faster than existing optimization-based methods. Additionally, to improve the sensing quality, we develop a mask optimization method based on the generic…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
