Interaction Dynamics Modeling and Predictive Control for Safe Steerable Catheter--Tissue Interaction

2026-07-23 · Source: Artificial Intelligence · Field: Technology & Digital — Robotics & Autonomous Systems, Artificial Intelligence & Machine Learning · Depth: Expert, quick

Summary

A new control method addresses safe steerable catheter operation by formulating catheter-tissue interaction dynamics in a scalar tip-normal coordinate. This approach tackles the complex problem of maintaining planned tip motion, ensuring compliance against moving tissue, rejecting friction and hysteresis, and adhering to a critical 0.5 N contact-force bound. The system uses a partial-physics feedforward to cancel nominal bending dynamics, revealing a configuration-invariant linear interaction-dynamics model. A predictive optimizer then regulates this interaction state, enforcing hard constraints on contact force, tendon force, and curvature. An augmented Kalman filter compresses errors into a sensor-free disturbance state, enabling offset-free regulation while explicitly managing force safety. In a MuJoCo simulation, disturbance augmentation reduced free-space approach error by 90%. The force-constrained predictive controller maintained contact force at 0.47 N, within the 0.5 N bound, even as an unconstrained controller reached 0.60 N at identical tracking. This safety was also demonstrated under 0.5 mm, 1.2 Hz cardiac motion. Hardware validation is future work.

Key takeaway

For robotics engineers developing steerable catheter control systems, this research demonstrates a robust method to achieve both precise motion and critical contact-force safety. By integrating predictive control with explicit hard constraints on contact force, tendon force, and curvature, your designs can reconcile tracking performance with clinical safety bounds. The augmented Kalman filter for disturbance estimation further enhances offset-free regulation. Consider adopting this interaction-dynamics approach to ensure catheter systems operate safely below the 0.5 N contact-force limit, even under dynamic cardiac motion.

Key insights

Predictive control with explicit force constraints enables safe, precise steerable catheter-tissue interaction.

Principles

• Catheter control is fundamentally an interaction dynamics problem.
• Offset-free motion regulation and contact-force safety are coupled objectives.
• Explicit predictive constraints resolve tension under stiff tissue contact.

Method

Formulate interaction dynamics in scalar tip-normal coordinates, use partial-physics feedforward, then a predictive optimizer with hard constraints, augmented by a Kalman filter for disturbance estimation.

In practice

• Reduce free-space approach error by 90% using disturbance augmentation.
• Maintain contact force below 0.5 N during tissue interaction.

Topics

• Steerable Catheters
• Predictive Control
• Interaction Dynamics
• Kalman Filter
• Medical Robotics
• Contact Force Control
• MuJoCo Simulation

Best for: AI Scientist, Robotics Engineer, AI Engineer, Research Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial Intelligence.