Fan, Wen and Li, Haoran and Si, Weiyong and Luo, Shan and Lepora, Nathan and Zhang, Dandan (2024) ViTacTip: Design and Verification of a Novel Biomimetic Physical Vision-Tactile Fusion Sensor. In: 2024 IEEE International Conference on Robotics and Automation (ICRA), 2024-05-13 - 2024-05-17, Yokohama, Japan.
Fan, Wen and Li, Haoran and Si, Weiyong and Luo, Shan and Lepora, Nathan and Zhang, Dandan (2024) ViTacTip: Design and Verification of a Novel Biomimetic Physical Vision-Tactile Fusion Sensor. In: 2024 IEEE International Conference on Robotics and Automation (ICRA), 2024-05-13 - 2024-05-17, Yokohama, Japan.
Fan, Wen and Li, Haoran and Si, Weiyong and Luo, Shan and Lepora, Nathan and Zhang, Dandan (2024) ViTacTip: Design and Verification of a Novel Biomimetic Physical Vision-Tactile Fusion Sensor. In: 2024 IEEE International Conference on Robotics and Automation (ICRA), 2024-05-13 - 2024-05-17, Yokohama, Japan.
Abstract
Tactile sensing is significant for robotics since it can obtain physical contact information during manipulation. To capture multimodal contact information within a compact framework, we designed a novel sensor called ViTacTip, which seamlessly integrates both tactile and visual perception capabilities into a single, integrated sensor unit. ViTacTip features a transparent skin to capture fine features of objects during contact, which can be known as the see-through-skin mechanism. In the meantime, the biomimetic tips embedded in ViTacTip can amplify touch motions during tactile perception. For comparative analysis, we also fabricated a ViTac sensor devoid of biomimetic tips, as well as a TacTip sensor with opaque skin. Furthermore, we develop a Generative Adversarial Network (GAN)-based approach for modality switching between different perception modes, effectively alternating the emphasis between vision and tactile perception modes. We conducted a performance evaluation of the proposed sensor across three distinct tasks: i) grating identification, ii) pose regression, iii) contact localization and force estimation. In the grating identification task, ViTacTip demonstrated an accuracy of 99.72%, surpassing TacTip, which achieved 94.60%. It also exhibited superior performance in both pose and force estimation tasks with the minimum error of 0.08 mm and 0.03N, respectively, in contrast to ViTac’s 0.12 mm and 0.15N. Results indicate that ViTacTip outperforms single-modality sensors.
Item Type: | Conference or Workshop Item (Paper) |
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Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 02 Oct 2024 14:28 |
Last Modified: | 02 Oct 2024 14:28 |
URI: | http://repository.essex.ac.uk/id/eprint/38967 |
Available files
Filename: 2402.00199v1.pdf