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Improving the Representation and Extraction of Contact Information in Vision-based Tactile Sensors Using Continuous Marker Pattern
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  • Mingxuan Li ,
  • Yen Hang Zhou ,
  • Tiemin Li ,
  • Yao Jiang
Mingxuan Li
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Yen Hang Zhou
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Tiemin Li
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Yao Jiang
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Abstract

Tactile perception has been a hot topic of research in robotics. Robots sense the shape, material, distributed force, slip during contact, and use the multi-modal contact information to control grasping and manipulation. For vision-based tactile sensors, the contact representation and extraction determine the quality of the raw tactile information, and therefore serve a significant role in the robot perception system. This article highlights for the first time the importance of raw representation and extraction in visuotactile perception, and proposes a new multicolor CMP method for enhancing the performance of vision-based tactile sensors. Based on the principle of continuous marker pattern (CMP), the multicolor CMP method is optimized in the pattern and algorithm design. Regarding information representation, we present a new type of marker pattern based on RGB triangles and a preferred layout. In terms of information extraction, we propose a series of extraction strategies with the adaptive growing algorithm (AGA) and the spin-search algorithm (SSA) as the cores. The experiments reveal that the multicolor CMP method achieves improved precision and reliability compared to the former CMP method.
Sep 2023Published in IEEE Robotics and Automation Letters volume 8 issue 9 on pages 6021-6028. 10.1109/LRA.2023.3303830