Leg loop Harness. Design and Method 4

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A Shell Model for Real-time Simulation of intra-ocular Implant Deployment

International audienceWith 30 million interventions a year worldwide, cataract surgery is one of the most frequently performed procedures. Yet, no tool currently allows teaching all steps of the procedure without putting pa- tients at risk. A particularly challenging stage of this surgery deals with the injection and deployment of the intra-ocular lens implant. In this paper we propose to rely on shell theory to accurately describe the com- plex deformations of the implant. Our approach extends the co-rotational method used in finite element analysis of in-plane deformations to incor- porate a bending energy. This results in a relatively simple and compu- tationally efficient approach which was applied to the simulation of the lens deployment. This simulation also accounts for the complex contacts that take place during the injection phase

Shell Model for Reconstruction and Real-Time Simulation of Thin Anatomical Structures

International audienceThis paper presents a new modelling technique for the defor- mation of thin anatomical structures like membranes and hollow organs. We show that the behaviour of this type of surface tissue can be ab- stracted with a modelling of their elastic resistance using shell theory. In order to apply the shell theory in the context of medical simulation, our method propose to base the geometrical reconstruction of the organ on the shape functions of the shell element. Moreover, we also use these continuous shape functions to handle the contacts and the interactions with other types of deformable tissues. The technique is illustrated using several examples including the simulation of an angioplasty procedure

Direct and inverse modeling of soft robots by learning a condensed FEM model

The Finite Element Method (FEM) is a powerful modeling tool for predicting the behavior of soft robots. However, its use for control can be difficult for non-specialists of numerical computation: it requires an optimization of the computation to make it real-time. In this paper, we propose a learning-based approach to obtain a compact but sufficiently rich mechanical representation. Our choice is based on nonlinear compliance data in the actuator/effector space provided by a condensation of the FEM model. We demonstrate that this compact model can be learned with a reasonable amount of data and, at the same time, be very efficient in terms of modeling, since we can deduce the direct and inverse kinematics of the robot. We also show how to couple some models learned individually in particular on an example of a gripper composed of two soft fingers. Other results are shown by comparing the inverse model derived from the full FEM model and the one from the compact learned version. This work opens new perspectives, namely for the embedded control of soft robots, but also for their design. These perspectives are also discussed in the paper

Potential exposure to diclofenac in Spain of European vultures

Diclofenac (NSAID) for veterinary use, the same that previously reduced south Asian Gyps vulture populations by nearly 99% in the late 1990s, was approved in Spain in 2013 for cattle, swine and horses. We assessed its availability and the potential exposure to European Griffon Gyps fulvus, Cinereous Aegypius monachus, Egyptian Neophron percnopterus and Bearded vultures Gypaetus barbatus in Spain. In 2014, a telephone questionnaire to 1073 official pharmaceutical distributers (POS) found 230 responses and 82 were currently selling diclofenac. The preliminary assessment for Spain showed a widespread exposure to diclofenac that extends across 275,391 km2, i.e. 54% of the territory. Diclofenac availability is related to livestock densities and certain rearing practices, especially cattle and extensive swine farming, but not with horse farms. Livestock farming carcass disposal practices and subsequent carcass availability to vultures are of concern when controlling for diclofenac potential use and residues in corpses. Overlap of diclofenac exposure with vulture distribution ranges and population sizes per region were highest for Cinereous Vulture (88% and 73% overlap with range and population size respectively), 62/56% for the Egyptian Vulture, 58/57% for the Griffon and 42/36% for the Bearded Vultures. Ensuring the safety of carcasses consumed by vultures with specific tests for NSAIDs and their use in farming practices is required

Projection-based model order reduction for real-time control of soft robots

International audienceSoft Robotics is a new field of robotics that deals with robots whose movements rely on the deformation of soft materials, such as silicone, rather than articulated rigid bodies in " traditional " robotics. Their design is often bio-inspired. Though having a great potential (for example in surgical applications, exploration of cavities, manipulation of fragile objects, etc…), one great challenge lies in their control since they are fundamentally equipped with a theoretically infinite number of degrees of freedom. Some works already proposed their control using a real-time finite element method [1]. The approach was limited by the real-time constraint which forced the use of relatively coarse meshes. This was good enough for a simple application with a unique effector. However, when considering complex geometries, more actuators and several effectors, finer meshes may be necessary, which would not be tractable in real-time. In this contribution, we attempt to perform real-time realistic simulation of the deformations of the soft robotics structures to achieve the real-time constraint with a converged mesh, meaning fine enough so that further refinement does not modify the result of the simulation. To this purpose, we use the snapshot-proper orthogonal decomposition (snapshot-POD), associated with an energy-conserving sampling and weighting (ECSW) method [2] to keep computational efficiency by only computing mechanical properties on a small subset of the finite elements. The parameter space explored in the offline stage is dictated by the range of the actuators of the soft-robot considered, as well as the possible contacts the robot may encounter. We show that we are able to achieve the real-time constraint with fine meshes. In further developments, if many actuators are involved, a specific sampling method based on Bayesian optimisation may be used to create the snapshot [3]. The main difficulty will lie on the fact that when the robot enters in contact with its environment, it may endure local deformations not captured by the reduced space. In this case, a partitioning strategy may be necessary [4], to allow for the computation of the local deformations with a full FEM model

Fast, generic and reliable control and simulation of soft robots using model order reduction

International audienceObtaining an accurate mechanical model of a soft deformable robot compatible with the computation time imposed by robotic applications is often considered as an unattainable goal. This paper should invert this idea. The proposed methodology offers the possibility to dramatically reduce the size and the online computation time of a Finite Element Model (FEM) of a soft robot. After a set of expensive offline simulations based on the whole model, we apply snapshot-proper orthogonal decomposition to sharply reduce the number of state variables of the soft robot model. To keep the computational efficiency, hyperre-duction is used to perform the integration on a reduced domain. The method allows to tune the error during the two main steps of complexity reduction. The method handles external loads (contact, friction, gravity...) with precision as long as they are tested during the offline simulations. The method is validated on two very different examples of FE models of soft robots and on one real soft robot. It enables acceleration factors of more than 100, while saving accuracy, in particular compared to coarsely meshed FE models and provides a generic way to control soft robots

An Open Source Design Optimization Toolbox Evaluated on a Soft Finger

In this paper, we introduce a novel open source toolbox for design optimization in Soft Robotics. We consider that design optimization is an important trend in Soft Robotics that is changing the way in which designs will be shared and adopted. We evaluate this toolbox on the example of a cable-driven, sensorized soft finger. For devices like these, that feature both actuation and sensing, the need for multi-objective optimization capabilities naturally arises, because at the very least, a trade-off between these two aspects has to be found. Thus, multi-objective optimization capability is one of the central features of the proposed toolbox. We evaluate the optimization of the soft finger and show that extreme points of the optimization trade-off between sensing and actuation are indeed far apart on actually fabricated devices for the established metrics. Furthermore, we provide an in depth analysis of the sim-to-real behavior of the example, taking into account factors such as the mesh density in the simulation, mechanical parameters and fabrication tolerances

Real-Time Simulation For Control Of Soft Robots With Self-Collisions Using Model Order Reduction For Contact Forces

International audienceIn rigid robotics, self-collision are usually avoided since it leads to a failure in the robot control and can also cause damage. In soft robotics, the situation is very different, and self-collisions may even be a desirable property, for example to gain artificial stiffness or to provide a natural limitation to the workspace. However, the modeling and simulation of self-collision is very costly as it requires first a collision detection algorithm to detect where collisions occur, and most importantly, it requires solving a constrained problem to avoid interpenetrations. When the number of contact points is large, this computation slows down the simulation dramatically. In this paper, we apply a numerical method to alleviate the contact response computation by reducing the contact space in a lowdimensional positive space obtained from experiments. We show good accuracy while speeding up dramatically the simulation. We apply the method in simulation on a cable-actuated finger and on a continuum manipulator performing exploration. We also show that the reduced contact method proposed can be used for inverse modeling. The method can therefore be used for control or design

Enabling the control of a new degree of freedom by using anisotropic material on a 6-DOF parallel soft robot

International audienceIn this paper, we design in simulation and build a parallel soft robot with a 6 degrees of freedom (DOF) endeffector. We show that by using a 3D-printed meso-structured material which displays an anisotropic behaviour, we can modify the kinematics of the structure in order to control one additional DOF which is not possible to achieve using a standard isotropic and homogeneous material like silicone. The behaviour of the robot is simulated using numerical homogenization and the finite element method (FEM), which runs in real-time and can be used for control. We finally show that the parallel soft robot we have built is controllable in open loop thanks to the use of inverse simulation. We demonstrate its maneuverability by guiding a marble in a maze game