Haptic Rendering of Hyperelastic Models with Friction

International audience— This paper presents an original method for inter-actions' haptic rendering when treating hyperelastic materials. Such simulations are known to be difficult due to the non-linear behavior of hyperelastic bodies; furthermore, haptic constraints enjoin contact forces to be refreshed at least at 1000 updates per second. To enforce the stability of simulations of generic objects of any range of stiffness, this method relies on implicit time integration. Soft tissues dynamics is simulated in real time (20 to 100 Hz) using the Multiplicative Jacobian Energy Decomposition (MJED) method. An asynchronous preconditioner, updated at low rates (1 to 10 Hz), is used to obtain a close approximation of the mechanical coupling of interactions. Finally, the contact problem is linearized and, using a specific-loop, it is updated at typical haptic rates (around 1000 Hz) allowing this way new simulations of prompt stiff-contacts and providing a continuous haptic feedback as well

Coupling numerical deformable models in global and reduced coordinates for the simulation of the direct and the inverse kinematics of Soft Robots

International audienceIn this paper, we propose a method to combine the Finite Element Method (FEM) with Discrete Cosserat Modeling (DCM) to capture the mechanics and the actuation of soft robots. The FEM is used to simulate the non-linear behavior of the volume of the soft structure while the cable/rod used for the actuation is modeled using the DCM. The two models are linked using kinematic constraints without imposing meshing rules. We demonstrate that both direct and inverse kinematic models can be obtained by quadratic optimization. The originality of this coupling is that the FEM model uses global coordinates (the position of the nodes of its mesh in space) where the Cosserat model uses local coordinates (successive strain values). The coupling of these mechanical models allows to combine the best of each parametrization. On the one hand, FEM allows to capture the behavior of the volume structure of the robot while accounting for its geometry with a complex mesh. On the other hand, the DCM allows efficient modeling of 1D structures such as rods, (concentric) tubes, cables, etc. that are used to deform the volume structure of the soft robots. DCM handles large deformation, torsion and (in)-extensibility and is efficient to compute. Moreover, the approach is compatible with complementarity constraints introduced when modeling contact and friction of the robot with its environment as well as the self-collision

Inverse real-time Finite Element simulation for robotic control of flexible needle insertion in deformable tissues

International audienceThis paper introduces a new method for automatic robotic needle steering in deformable tissues. The main contribution relies on the use of an inverse Finite Element (FE) simulation to control an articulated robot interacting with deformable structures. In this work we consider a flexible needle, embedded in the end effector of a 6 arm Mitsubishi RV1A robot, and its insertion into a silicone phantom. Given a trajectory on the rest configuration of the silicone phantom, our method provides in real-time the displacements of the articulated robot which guarantee the permanence of the needle within the predefined path, taking into account any undergoing deformation on both the needle and the trajectory itself. A forward simulation combines i) a kinematic model of the robot, ii) FE models of the needle and phantom gel iii) an interaction model allowing the simulation of friction and puncture force. A Newton-type method is then used to provide the displacement of the robot to minimize the distance between the needle's tip and the desired trajectory. We validate our approach with a simulation in which a virtual robot can successfully perform the insertion while both the needle and the trajectory undergo significant deformations

Silhouette-based Pose Estimation for Deformable Organs Application to Surgical Augmented Reality

International audience— In this paper we introduce a method for semi-automatic registration of 3D deformable models using 2D shape outlines (silhouettes) extracted from a monocular camera view. Our framework is based on the combination of a biomechanical model of the organ with a set of projective constraints influencing the deformation of the model. To enforce convergence towards a global minimum for this ill-posed problem we interactively provide a rough (rigid) estimation of the pose. We show that our approach allows for the estimation of the non-rigid 3D pose while relying only on 2D information. The method is evaluated experimentally on a soft silicone gel model of a liver, as well as on real surgical data, providing augmented reality of the liver and the kidney using a monocular laparoscopic camera. Results show that the final elastic registration can be obtained in just a few seconds, thus remaining compatible with clinical constraints. We also evaluate the sensitivity of our approach according to both the initial alignment of the model and the silhouette length and shape

Domain Decomposition for real time Simulation of needle insertion

International audienceOur goal is to develop robotized needle insertion for drug delivery in small animals. We control the robot with a real-time Finite Element simulation that provides accurate models of the deformable environment. To predict the deformations we need to solve a contact problem which is known to be time consuming. To reduce the computational time we use the domain decomposition method: the FE mesh is split in several domains in order to extract paral-lelism for GPU computing and to concentrate the computation time around the needle

Marker-based Registration for Large Deformations -Application to Open Liver Surgery

International audienceThis paper introduces an Augmented Reality (AR) system for open liver surgery. Although open surgery remains the gold-standard for the treatment of complex tumors and central lesions, technological issues actually prevent using AR with sufficient accuracy for clinical use. We propose a markers-based method allowing for the tracking and the deformation of a preoperative model in real-time during the surgery. Markers are manually placed on the surface of the organ after opening the abdominal cavity, and tracked in real-time by a set of infrared cameras. Our framework is composed of both a non-rigid initial registration method, providing an estimation of the location of the markers in the preoperative model, and a real-time tracking algorithm to deform the model during the surgery (even for large deformation or partial occlusion of the organ). The method is validated on both synthetic and ex-vivo samples; in addition, we demonstrate its applicability in the operating room during a liver resection surgery on a human patient. Preliminary studies provided promising results to improve the location of tumors, and to help surgeons into planning the ideal resection intraoperatively

Domain Decomposition for real time Simulation of needle insertion

International audienceOur goal is to develop robotized needle insertion for drug delivery in small animals. We control the robot with a real-time Finite Element simulation that provides accurate models of the deformable environment. To predict the deformations we need to solve a contact problem which is known to be time consuming. To reduce the computational time we use the domain decomposition method: the FE mesh is split in several domains in order to extract paral-lelism for GPU computing and to concentrate the computation time around the needle

Coupling robotics and medical simulations for automatic percutaneous procedures

Les techniques d'insertion d'aiguille font partie des interventions chirurgicales les plus courantes. L'efficacité de ces interventions dépend fortement de la précision du positionnement des aiguilles dans un emplacement cible à l'intérieur du corps du patient. L'objectif principal dans cette thèse est de développer un système robotique autonome, capable d'insérer une aiguille flexible dans une structure déformable le long d'une trajectoire prédéfinie. L’originalité de ce travail se trouve dans l’utilisation de simulations inverses par éléments finis (EF) dans la boucle de contrôle du robot pour prédire la déformation des structures. La particularité de ce travail est que pendant l’insertion, les modèles EF sont continuellement recalés (étape corrective) grâce à l’information extraite d’un système d’imagerie peropératoire. Cette étape permet de contrôler l’erreur des modèles par rapport aux structures réelles et ainsi éviter qu'ils divergent. Une seconde étape (étape de prédiction) permet, à partir de la position corrigée, d’anticiper le comportement de structures déformables, en se reposant uniquement sur les prédictions des modèles biomécaniques. Ceci permet ainsi d’anticiper la commande du robot pour compenser les déplacements des tissus avant même le déplacement de l’aiguille. Expérimentalement, nous avions utilisé notre approche pour contrôler un robot réel afin d'insérer une aiguille flexible dans une mousse déformable le long d'une trajectoire (virtuelle) prédéfinie. Nous avons proposé une formulation basée sur des contraintes permettant le calcul d'étapes prédictives dans l'espace de contraintes offrant ainsi un temps d'insertion total compatible avec les applications cliniques. Nous avons également proposé un système de réalité augmentée pour la chirurgie du foie ouverte. La méthode est basée sur un recalage initial semi-automatique et un algorithme de suivi peropératoire basé sur des marqueurs (3D) optiques. Nous avons démontré l'applicabilité de cette approche en salle d'opération lors d'une chirurgie de résection hépatique. Les résultats obtenus au cours de ce travail de thèse ont conduit à trois publications (deux IROS et un ICRA) dans les conférences internationales puis à un journal (Transactions on Robotics) en cours de révision.Needle-based interventions are among the least invasive surgical approaches to access deep internal structures into organs' volumes without damaging surrounding tissues. Unlike traditional open surgery, needle-based approaches only affect a localized area around the needle, reducing this way the occurrence of traumas and risks of complications \cite{Cowan2011}. Many surgical procedures rely on needles in nowadays clinical routines (biopsies, local anesthesia, blood sampling, prostate brachytherapy, vertebroplasty ...). Radiofrequency ablation (RFA) is an example of percutaneous procedure that uses heat at the tip of a needle to destroy cancer cells. Such alternative treatments may open new solutions for unrespectable tumors or metastasis (concerns about the age of the patient, the extent or localization of the disease). However, contrary to what one may think, needle-based approaches can be an exceedingly complex intervention. Indeed, the effectiveness of the treatment is highly dependent on the accuracy of the needle positioning (about a few millimeters) which can be particularly challenging when needles are manipulated from outside the patient with intra-operative images (X-ray, fluoroscopy or ultrasound ...) offering poor visibility of internal structures. Human factors, organs' deformations, needle deflection and intraoperative imaging modalities limitations can be causes of needle misplacement and rise significantly the technical level necessary to master these surgical acts. The use of surgical robots has revolutionized the way surgeons approach minimally invasive surgery. Robots have the potential to overcome several limitations coming from the human factor: for instance by filtering operator tremors, scaling the motion of the user or adding new degrees of freedom at the tip of instruments. A rapidly growing number of surgical robots has been developed and applied to a large panel of surgical applications \cite{Troccaz2012}. Yet, an important difficulty for needle-based procedures lies in the fact that both soft tissues and needles tend to deform as the insertion proceeds in a way that cannot be described with geometrical approaches. Standard solutions address the problem of the deformation extracting a set of features from per-operative images (also called \textit{visual servoing)} and locally adjust the pose/motion of the robot to compensate for deformations \cite{Hutchinson1996}. [...]To overcome these limitations, we introduce a numerical method allowing performing inverse Finite Element simulations in real-time. We show that it can be used to control an articulated robot while considering deformations of structures during needle insertion. Our approach relies on a forward FE simulation of a needle insertion (involving complex non-linear phenomena such as friction, puncture and needle constraints).[...

Couplage de la rObotique et de la simulatioN mEdical pour des proCédures automaTisées (CONECT)

Needle-based interventions are among the least invasive surgical approaches to access deep internal structures into organs' volumes without damaging surrounding tissues. Unlike traditional open surgery, needle-based approaches only affect a localized area around the needle, reducing this way the occurrence of traumas and risks of complications \cite{Cowan2011}. Many surgical procedures rely on needles in nowadays clinical routines (biopsies, local anesthesia, blood sampling, prostate brachytherapy, vertebroplasty ...). Radiofrequency ablation (RFA) is an example of percutaneous procedure that uses heat at the tip of a needle to destroy cancer cells. Such alternative treatments may open new solutions for unrespectable tumors or metastasis (concerns about the age of the patient, the extent or localization of the disease). However, contrary to what one may think, needle-based approaches can be an exceedingly complex intervention. Indeed, the effectiveness of the treatment is highly dependent on the accuracy of the needle positioning (about a few millimeters) which can be particularly challenging when needles are manipulated from outside the patient with intra-operative images (X-ray, fluoroscopy or ultrasound ...) offering poor visibility of internal structures. Human factors, organs' deformations, needle deflection and intraoperative imaging modalities limitations can be causes of needle misplacement and rise significantly the technical level necessary to master these surgical acts. The use of surgical robots has revolutionized the way surgeons approach minimally invasive surgery. Robots have the potential to overcome several limitations coming from the human factor: for instance by filtering operator tremors, scaling the motion of the user or adding new degrees of freedom at the tip of instruments. A rapidly growing number of surgical robots has been developed and applied to a large panel of surgical applications \cite{Troccaz2012}. Yet, an important difficulty for needle-based procedures lies in the fact that both soft tissues and needles tend to deform as the insertion proceeds in a way that cannot be described with geometrical approaches. Standard solutions address the problem of the deformation extracting a set of features from per-operative images (also called \textit{visual servoing)} and locally adjust the pose/motion of the robot to compensate for deformations \cite{Hutchinson1996}. [...]To overcome these limitations, we introduce a numerical method allowing performing inverse Finite Element simulations in real-time. We show that it can be used to control an articulated robot while considering deformations of structures during needle insertion. Our approach relies on a forward FE simulation of a needle insertion (involving complex non-linear phenomena such as friction, puncture and needle constraints).[...]Les techniques d'insertion d'aiguille font partie des interventions chirurgicales les plus courantes. L'efficacité de ces interventions dépend fortement de la précision du positionnement des aiguilles dans un emplacement cible à l'intérieur du corps du patient. L'objectif principal dans cette thèse est de développer un système robotique autonome, capable d'insérer une aiguille flexible dans une structure déformable le long d'une trajectoire prédéfinie. L’originalité de ce travail se trouve dans l’utilisation de simulations inverses par éléments finis (EF) dans la boucle de contrôle du robot pour prédire la déformation des structures. La particularité de ce travail est que pendant l’insertion, les modèles EF sont continuellement recalés (étape corrective) grâce à l’information extraite d’un système d’imagerie peropératoire. Cette étape permet de contrôler l’erreur des modèles par rapport aux structures réelles et ainsi éviter qu'ils divergent. Une seconde étape (étape de prédiction) permet, à partir de la position corrigée, d’anticiper le comportement de structures déformables, en se reposant uniquement sur les prédictions des modèles biomécaniques. Ceci permet ainsi d’anticiper la commande du robot pour compenser les déplacements des tissus avant même le déplacement de l’aiguille. Expérimentalement, nous avions utilisé notre approche pour contrôler un robot réel afin d'insérer une aiguille flexible dans une mousse déformable le long d'une trajectoire (virtuelle) prédéfinie. Nous avons proposé une formulation basée sur des contraintes permettant le calcul d'étapes prédictives dans l'espace de contraintes offrant ainsi un temps d'insertion total compatible avec les applications cliniques. Nous avons également proposé un système de réalité augmentée pour la chirurgie du foie ouverte. La méthode est basée sur un recalage initial semi-automatique et un algorithme de suivi peropératoire basé sur des marqueurs (3D) optiques. Nous avons démontré l'applicabilité de cette approche en salle d'opération lors d'une chirurgie de résection hépatique. Les résultats obtenus au cours de ce travail de thèse ont conduit à trois publications (deux IROS et un ICRA) dans les conférences internationales puis à un journal (Transactions on Robotics) en cours de révision

Coupling robotics and medical simulations for automatic percutaneous procedures

Les techniques d'insertion d'aiguille font partie des interventions chirurgicales les plus courantes. L'efficacité de ces interventions dépend fortement de la précision du positionnement des aiguilles dans un emplacement cible à l'intérieur du corps du patient. L'objectif principal dans cette thèse est de développer un système robotique autonome, capable d'insérer une aiguille flexible dans une structure déformable le long d'une trajectoire prédéfinie. L’originalité de ce travail se trouve dans l’utilisation de simulations inverses par éléments finis (EF) dans la boucle de contrôle du robot pour prédire la déformation des structures. La particularité de ce travail est que pendant l’insertion, les modèles EF sont continuellement recalés (étape corrective) grâce à l’information extraite d’un système d’imagerie peropératoire. Cette étape permet de contrôler l’erreur des modèles par rapport aux structures réelles et ainsi éviter qu'ils divergent. Une seconde étape (étape de prédiction) permet, à partir de la position corrigée, d’anticiper le comportement de structures déformables, en se reposant uniquement sur les prédictions des modèles biomécaniques. Ceci permet ainsi d’anticiper la commande du robot pour compenser les déplacements des tissus avant même le déplacement de l’aiguille. Expérimentalement, nous avions utilisé notre approche pour contrôler un robot réel afin d'insérer une aiguille flexible dans une mousse déformable le long d'une trajectoire (virtuelle) prédéfinie. Nous avons proposé une formulation basée sur des contraintes permettant le calcul d'étapes prédictives dans l'espace de contraintes offrant ainsi un temps d'insertion total compatible avec les applications cliniques. Nous avons également proposé un système de réalité augmentée pour la chirurgie du foie ouverte. La méthode est basée sur un recalage initial semi-automatique et un algorithme de suivi peropératoire basé sur des marqueurs (3D) optiques. Nous avons démontré l'applicabilité de cette approche en salle d'opération lors d'une chirurgie de résection hépatique. Les résultats obtenus au cours de ce travail de thèse ont conduit à trois publications (deux IROS et un ICRA) dans les conférences internationales puis à un journal (Transactions on Robotics) en cours de révision.Needle-based interventions are among the least invasive surgical approaches to access deep internal structures into organs' volumes without damaging surrounding tissues. Unlike traditional open surgery, needle-based approaches only affect a localized area around the needle, reducing this way the occurrence of traumas and risks of complications \cite{Cowan2011}. Many surgical procedures rely on needles in nowadays clinical routines (biopsies, local anesthesia, blood sampling, prostate brachytherapy, vertebroplasty ...). Radiofrequency ablation (RFA) is an example of percutaneous procedure that uses heat at the tip of a needle to destroy cancer cells. Such alternative treatments may open new solutions for unrespectable tumors or metastasis (concerns about the age of the patient, the extent or localization of the disease). However, contrary to what one may think, needle-based approaches can be an exceedingly complex intervention. Indeed, the effectiveness of the treatment is highly dependent on the accuracy of the needle positioning (about a few millimeters) which can be particularly challenging when needles are manipulated from outside the patient with intra-operative images (X-ray, fluoroscopy or ultrasound ...) offering poor visibility of internal structures. Human factors, organs' deformations, needle deflection and intraoperative imaging modalities limitations can be causes of needle misplacement and rise significantly the technical level necessary to master these surgical acts. The use of surgical robots has revolutionized the way surgeons approach minimally invasive surgery. Robots have the potential to overcome several limitations coming from the human factor: for instance by filtering operator tremors, scaling the motion of the user or adding new degrees of freedom at the tip of instruments. A rapidly growing number of surgical robots has been developed and applied to a large panel of surgical applications \cite{Troccaz2012}. Yet, an important difficulty for needle-based procedures lies in the fact that both soft tissues and needles tend to deform as the insertion proceeds in a way that cannot be described with geometrical approaches. Standard solutions address the problem of the deformation extracting a set of features from per-operative images (also called \textit{visual servoing)} and locally adjust the pose/motion of the robot to compensate for deformations \cite{Hutchinson1996}. [...]To overcome these limitations, we introduce a numerical method allowing performing inverse Finite Element simulations in real-time. We show that it can be used to control an articulated robot while considering deformations of structures during needle insertion. Our approach relies on a forward FE simulation of a needle insertion (involving complex non-linear phenomena such as friction, puncture and needle constraints).[...