ICRA 2021 Workshop

Research /

Learning robotic needle steering from inverse finite element simulations

Tissue motion compensation during robotic needle steering is a challenging research topic. While the deformable non-linear coupling between needle and tissue is captured by simulation-based control strategies, they increase significantly the computational cost of the control. In this work, we rely on machine learning methods to enable autonomous robotic needle steering with very low computation times. We propose to use an Extreme Learning Machine (ELM) to learn an inverse model which accounts for needle-tissue interaction. The ELM trains with synthetic data generated from multiple needle insertions controlled by inverse finite-element simulations.

EUROGRAPHICS 2021

Research /

Interactive Finite Element model of needle insertion and laceration

This paper introduces an interactive model of needle insertion, including the possibility to simulate lacerations of tissue around the needle. The method relies on complementary constraints to couple the Finite Element models of the needle and tissue. The cutting path is generated from mechanical criteria (i.e. cutting force) at arbitrary resolution, avoiding expensive remeshing of Finite Element meshes. Complex behavior can be simulated in real time such as friction along the shaft of the needle, puncture and cutting force resulting from interactions of the needle with the tissue

ICRA 2021

Research /

Shared control strategy for needle insertion into deformable tissue using inverse Finite Element simulation

This paper deals with the problem of needle steering in deformable tissues subject to physiological motions. A novel shared control method is proposed, which combines an automatic needle steering algorithm with the motions applied by the radiologist, in order to place the needle tip at the desired location. The core motivation is to leave potentially dangerous decisions and actions to the practitioner, whereas complex nonintuitive manipulations of the needle are performed automatically, in particular to compensate for breathing motions. The most original part of the present work lies in the method used to combine user inputs with a closed-loop automatic needle steering control method based on inverse Finite Element simulations

ICRA 2020

Research /

Robotic needle insertion in moving soft tissues