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Non-Rigid Motion Compensation with Skin Deformation Prediction for in Situ Bioprinting

Lénaïc Cuau, Philippe Poignet, Nabil Zemiti

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Key figure (auto-extracted from paper)
A novel vision- and laser-based compensation method enables precise in situ bioprinting on deforming tissue, reducing wound coverage error to under 1%.
In situ bioprinting non-rigid motion compensation visual servoing skin deformation prediction medical robotics

Problem

Existing in situ bioprinting platforms lack real-time compensation for non-rigid patient motion, risking safety and wound coverage. Current methods fail to simultaneously control tool distance, orientation, and position on deforming surfaces.

Approach

The system uses an RGB-D camera to predict skin deformation via a Thin Plate Spline model and Kalman filtering, while a laser telemeter regulates layer height and visual servoing maintains perpendicular nozzle orientation.

Key results

  • Wound coverage error under 1%
  • 73% improvement in deforming path following
  • Layer height control error below 0.1 mm
  • Real-time orientation tracking with mean error under 4°

Why it matters

Enables safer, more precise robotic skin deposition for burn reconstruction and other clinical applications where patient motion is unavoidable.

Abstract

This letter introduces a novel method of non-rigid motion compensation for in situ bioprinting. Most bioprinting plat- forms use open-loop systems, but it raises concerns about patient safety and suboptimal wound coverage in case of patient motion. To handle these issues, our method integrates an RGB-D camera to manage orientation and to predict deformations, along with a laser telemeter to regulate deposited material thickness. The proposed approach has been evaluated on a moving silicone platform that deforms at 0.8 Hz with a 4 mm in-plane amplitude and a 20 mm elevation amplitude. Our method resulted in a wound coverage error of less than 1%. Comparative analysis demonstrates a 73.0% enhancement in deforming path following compared to existing methods. Additionally, by predicting surface motion, the method enables more precise control of layer height, with an error inferior to 0.1mm.

Index terms

Medical Robots and Systems Motion and Path Planning Visual Servoing

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