Friction Estimation for In-Hand Planar Motion

2025-07-09

AI Summary

Estimating contact properties—specifically static friction coefficient, Coulomb friction coefficient, and contact radius—during in-hand planar sliding remains challenging due to their time-varying nature and lack of direct observability. To address this, we propose an online identification method leveraging real-time tactile force and sliding velocity feedback. Our approach builds upon a gripper–object dynamic model and integrates tactile sensor measurements with a heuristic parameter update strategy tailored for rapid stick–slip transitions, thereby significantly improving estimation stability and accuracy during transient sliding. The method requires no prior calibration or assumptions about contact geometry, ensuring both physical interpretability and computational efficiency. Simulation and physical experiments demonstrate millisecond-level response time and estimation errors below 8%, validating its high fidelity and robustness. This work establishes a reliable perceptual foundation for adaptive sliding control in dexterous robotic hands.

Technology Category

• Intelligent Robots: State Estimation
• Planning, Routing, and Scheduling: Activity and Plan Recognition
• Computer Vision: Low Level & Physics-based Vision

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

This paper presents a method for online estimation of contact properties during in-hand sliding manipulation with a parallel gripper. We estimate the static and Coulomb friction as well as the contact radius from tactile measurements of contact forces and sliding velocities. The method is validated in both simulation and real-world experiments. Furthermore, we propose a heuristic to deal with fast slip-stick dynamics which can adversely affect the estimation.

Problem

• Estimates static and Coulomb friction during in-hand sliding
• Determines contact radius from tactile force and velocity data
• Addresses slip-stick dynamics to improve estimation accuracy

Innovation

• Online estimation of static and Coulomb friction
• Contact radius from tactile force measurements
• Heuristic for handling fast slip-stick dynamics