DelTact: A Vision-based Tactile Sensor Using Dense Color Pattern
Guanlan Zhang, Yipai Du, Hongyu Yu, Michael Yu Wang

TL;DR
DelTact is a compact, high-resolution vision-based tactile sensor that uses an optimized dense color pattern and optical flow to accurately measure contact shape and force distribution in real-time.
Contribution
The paper introduces DelTact, a novel tactile sensor with a modular design, dense color pattern optimization, and real-time contact measurement capabilities.
Findings
High accuracy in contact deformation tracking
Low error tactile measurements at 40Hz
Effective extraction of contact shape and force distribution
Abstract
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 performance in manipulation and grasping. Here we propose a new design of a vision-based tactile sensor, DelTact. The sensor uses a modular hardware architecture for compactness whilst maintaining a contact measurement of full resolution (798*586) and large area (675mm2). Moreover, it adopts an improved dense random color pattern based on the previous version to achieve high accuracy of contact deformation tracking. In particular, we optimize the color pattern generation process and select the appropriate pattern for coordinating with a dense optical flow algorithm under a real-world experimental sensory setting. The optical flow obtained from the raw image is processed to determine shape and force…
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.
Taxonomy
TopicsAdvanced Sensor and Energy Harvesting Materials · Tactile and Sensory Interactions · Robot Manipulation and Learning
