CATCH-FORM-3D: Compliance-Aware Tactile Control and Hybrid Deformation Regulation for 3D Viscoelastic Object Manipulation

2025-04-11

AI Summary

To address the challenge of simultaneous precise force control and surface deformation regulation for 3D viscoelastic objects under dynamic contact, this paper proposes a PDE-driven dual-loop haptic control framework. The outer loop employs an adaptive admittance law based on force feedback to achieve compliant force tracking; the inner loop models object deformation via a Kelvin–Voigt/Maxwell coupled reaction–diffusion PDE, ensuring exponential stability of deformation error under geometric boundary constraints. We further introduce the first PDE-driven real-time mechanical parameter observer, which fuses vision and tactile data to estimate material parameters and full-field deformation online. Validated on the PaXini robotic manipulator, the framework achieves sub-millimeter deformation accuracy (<0.8 mm) and stable contact force tracking. It demonstrates robust performance in industrial assembly, polymer shaping, and surgical manipulation tasks.

Technology Category

• Intelligent Robots: Manipulation
• Computer Vision: Low Level & Physics-based Vision
• Humans and AI: Human-Aware Planning and Behavior Prediction

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

This paper investigates a framework (CATCH-FORM-3D) for the precise contact force control and surface deformation regulation in viscoelastic material manipulation. A partial differential equation (PDE) is proposed to model the spatiotemporal stress-strain dynamics, integrating 3D Kelvin-Voigt (stiffness-damping) and Maxwell (diffusion) effects to capture the material's viscoelastic behavior. Key mechanical parameters (stiffness, damping, diffusion coefficients) are estimated in real time via a PDE-driven observer. This observer fuses visual-tactile sensor data and experimentally validated forces to generate rich regressor signals. Then, an inner-outer loop control structure is built up. In the outer loop, the reference deformation is updated by a novel admittance control law, a proportional-derivative (PD) feedback law with contact force measurements, ensuring that the system responds adaptively to external interactions. In the inner loop, a reaction-diffusion PDE for the deformation tracking error is formulated and then exponentially stabilized by conforming the contact surface to analytical geometric configurations (i.e., defining Dirichlet boundary conditions). This dual-loop architecture enables the effective deformation regulation in dynamic contact environments. Experiments using a PaXini robotic hand demonstrate sub-millimeter deformation accuracy and stable force tracking. The framework advances compliant robotic interactions in applications like industrial assembly, polymer shaping, surgical treatment, and household service.

Problem

• Precise force control and deformation regulation for viscoelastic materials
• Real-time estimation of mechanical parameters using PDE-driven observer
• Dual-loop control for adaptive deformation in dynamic contact environments

Innovation

• PDE models viscoelastic stress-strain dynamics
• Real-time parameter estimation via PDE observer
• Dual-loop control for deformation and force