A Passive Variable Impedance Control Strategy with Viscoelastic Parameters Estimation of Soft Tissues for Safe Ultrasonography

TL;DR

This work tackles safe robot-assisted ultrasonography by addressing how a probe interacts with diverse soft tissues. It integrates offline viscoelastic tissue parameter estimation using the Hunt-Crossley model and GP-based tissue maps with a port-Hamiltonian, energy-tank framework to enable online QP-based impedance adaptation. Two strategies, VS-CF and VS-VF, balance precise force tracking with safe penetration bounds. Experimental validation on a dummy chest shows improved safety and force-tracking performance over baseline controllers, highlighting practical potential for lung/heart ultrasound where ribs and soft tissues pose safety challenges.

Abstract

In the context of telehealth, robotic approaches have proven a valuable solution to in-person visits in remote areas, with decreased costs for patients and infection risks. In particular, in ultrasonography, robots have the potential to reproduce the skills required to acquire high-quality images while reducing the sonographer's physical efforts. In this paper, we address the control of the interaction of the probe with the patient's body, a critical aspect of ensuring safe and effective ultrasonography. We introduce a novel approach based on variable impedance control, allowing real-time optimisation of a compliant controller parameters during ultrasound procedures. This optimisation is formulated as a quadratic programming problem and incorporates physical constraints derived from viscoelastic parameter estimations. Safety and passivity constraints, including an energy tank, are also integrated to minimise potential risks during human-robot interaction. The proposed method's efficacy is demonstrated through experiments on a patient dummy torso, highlighting its potential for achieving safe behaviour and accurate force control during ultrasound procedures, even in cases of contact loss.

Figures (7)

• Figure 1: Experimental setup.
• Figure 2: Load tests obtained with the different models.
• Figure 3: Variation of residual as palpation time changes.
• Figure 4: Resulting maps from the GPR computing the values of elasticity and viscosity every $0.1mm$.
• Figure 5: Surface reconstruction with elasticity information. The view is rotated of 180° degrees wrt \ref{['fig:stiffdamp_map']} to better show the shape of the body.