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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.02026 |
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| _version_ | 1866917324043321344 |
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| author | Niu, Zhenwei Chen, Xiaoyi Hu, Jiayu Liu, Zhaoyang Jian, Tang Ju, Xiaozu |
| author_facet | Niu, Zhenwei Chen, Xiaoyi Hu, Jiayu Liu, Zhaoyang Jian, Tang Ju, Xiaozu |
| contents | We introduce a unified framework for gentle robotic grasping that synergistically couples real-time friction estimation with adaptive grasp control. We propose a new particle filter-based method for real-time estimation of the friction coefficient using vision-based tactile sensors. This estimate is seamlessly integrated into a reactive controller that dynamically modulates grasp force to maintain a stable grip. The two processes operate synchronously in a closed-loop: the controller uses the current best estimate to adjust the force, while new tactile feedback from this action continuously refines the estimation. This creates a highly responsive and robust sensorimotor cycle. The reliability and efficiency of the complete framework are validated through extensive robotic experiments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_02026 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Synchronized Online Friction Estimation and Adaptive Grasp Control for Robust Gentle Grasp Niu, Zhenwei Chen, Xiaoyi Hu, Jiayu Liu, Zhaoyang Jian, Tang Ju, Xiaozu Robotics We introduce a unified framework for gentle robotic grasping that synergistically couples real-time friction estimation with adaptive grasp control. We propose a new particle filter-based method for real-time estimation of the friction coefficient using vision-based tactile sensors. This estimate is seamlessly integrated into a reactive controller that dynamically modulates grasp force to maintain a stable grip. The two processes operate synchronously in a closed-loop: the controller uses the current best estimate to adjust the force, while new tactile feedback from this action continuously refines the estimation. This creates a highly responsive and robust sensorimotor cycle. The reliability and efficiency of the complete framework are validated through extensive robotic experiments. |
| title | Synchronized Online Friction Estimation and Adaptive Grasp Control for Robust Gentle Grasp |
| topic | Robotics |
| url | https://arxiv.org/abs/2602.02026 |