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Synchronized Online Friction Estimation and Adaptive Grasp Control for Robust Gentle Grasp

2026-02-02 · Zhenwei Niu, Xiaoyi Chen, Jiayu Hu, Zhaoyang Liu, Tang Jian, Xiaozu Ju arxiv

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.

📄 PDF Abstract BibTeX arXiv:2602.02026

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Robotic Grasping

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