Adaptive merging for rigid body simulation.
E. Coevoet, O. Benchekroun, and P.G. Kry
SIGGRAPH 2020
We reduce computation time in rigid body simulations by merging collections of bodies when they share a common spatial velocity. Merging relies on monitoring the state of contacts, and a metric that compares the relative linear and angular motion of bodies based on their sizes. Unmerging relies on an inexpensive single iteration projected Gauss-Seidel sweep over contacts between merged bodies, which lets us update internal contact forces over time, and use the same metrics as merging to identify when bodies should unmerge. Furthermore we use a contact ordering for graph traversal refinement of the internal contact forces in collections, which helps to correctly identify all the bodies that must unmerge when there are impacts. The general concept of merging is similar to the common technique of sleeping and waking rigid bodies in the inertial frame, and we exploit this too, but our merging is in moving frames, and unmerging takes place at contacts between bodies rather than at the level of bodies themselves. We discuss the previous relative motion metrics in comparison to ours, and evaluate our method on a variety of scenarios.
Soft robots locomotion and manipulation control using FEM
simulation and quadratic programming.
E. Coevoet, A. Escande, and C. Duriez
RoboSoft 2019
In this paper, we propose a method to control the motion of soft robots able to manipulate objects or roll from one place to another. We use the Finite Element Method (FEM) to simulate the deformations of the soft robot, its actuators, and surroundings when deformable. To find the inverse model of the robot interacting with obstacles, and with constraints on its actuators, we write the problem as a quadratic program with complementarity constraints. The novelty of this work is that friction contacts (sticking contact only) are taken into account in the optimization process, allowing the control of these specific tasks that are locomotion and manipulation. We propose a formulation that simplifies the optimization problem, together with a dedicated solver. The algorithm has real-time performance and handles evolving environments as long as we know them. To show the effectiveness of the method, we present several numerical examples, and a demonstration on a real robot.
Optimization-based inverse model of soft robots with contact handling.
Commitee: François Chaumette (Chair), Jamie Paik (Reviewer), Nicolas Mansard (Reviewer), Allison Okamura (Examiner), Hadrien Courtecuisse (Examiner), Adrien Escande (Examiner), Christian Duriez (Supervisor)
Ph.D Thesis 2019
Soft robotics draws its inspiration from nature, from the way living organisms move and adapt their shape to their environment. In opposition to traditional rigid robots, soft robots are built from highly compliant materials, allowing them to accomplish tasks with more flexibility and adaptability. They are safer when working in fragile environment. They have the advantages of producing low forces that are suitable for manipulating/interacting with sensitive objects/surroundings without harming them. These characteristics allow for potential use of soft robotics in the fields of manufacturing and medicine. But the field of soft robotics brings new challenges, in particular for modeling and control. Within this thesis we aim at providing generic methods for soft robot modeling, without assumptions on the geometry. The methods are based on the finite element method to capture the deformations of the robot’s structure and of its environment when deformable. We formulate the problem of their inverse kinematics and dynamics as optimization programs, allowing easy handling of constraints on actuation and singularity problems. Weareable to control several types of actuation, such as cable, pneumatic and hydraulic actuations. Moreover, most of the applications involve interaction of the robot with obstacles. Yet soft robots kinematics is highly dependent on environmental factors. We propose new methods that include contacts into the optimization process. These methods make an important step as we think that the knowledge of contacts in the modeling is all the more important. Finally, we propose to control some soft robots during locomotion and grasping tasks which require the use of contact with static friction. We give a particular attention to provide solutions with real-time performance, allowing online control in evolving environments.
FEM-based deformation control for dexterous manipulation of 3D soft objects.
F. Ficuciello, A. Migliozzi, E. Coevoet, A. Petit, and C. Duriez
IROS 2018
In this paper, a method for dexterous manipulation of 3D soft objects for real-time deformation control is presented, relying on Finite Element modelling. The goal is to generate proper forces on the fingertips of an anthropomorphic device during in-hand manipulation to produce desired displacements of selected control points on the object. The desired motions of the fingers are computed in real-time as an inverse solution of a Finite Element Method (FEM), the forces applied by the fingertips at the contact points being modeled by Lagrange multipliers. The elasticity parameters of the model are preliminary estimated using a vision system and a force sensor. Experimental results are shown with an under-actuated anthropomorphic hand that performs a manipulation task on a soft cylindrical object.
Software toolkit for modeling, simulation and control of soft robots.
E. Coevoet, T. Morales-Bieze, F. Largilliere et. al
Advanced Robotics 2017 ★best paper award
The technological differences between traditional robotics and soft robotics have an impact on all of the modeling tools generally in use, including direct kinematics and inverse models, Jacobians, and dynamics. Due to the lack of precise modeling and control methods for soft robots, the promising concepts of using such design for complex applications (medicine, assistance, domestic robotics…) cannot be practically implemented. This paper presents a first unified software framework dedicated to modeling, simulation and control of soft robots. The framework relies on continuum mechanics for modeling the robotic parts and boundary conditions like actuators or contacts using a unified representation based on Lagrange multipliers. It enables the digital robot to be simulated in its environment using a direct model. The model can also be inverted online using an optimization-based method which allows to control the physical robots in the task space. To demonstrate the effectiveness of the approach, we present various soft robots scenarios including ones where the robot is interacting with its environment. The software has been built on top of SOFA, an open-source framework for deformable online simulation and is available at https://project.inria.fr/softrobot/
Optimization-based inverse model of soft robots with contact handling.
E. Coevoet, A. Escande, and C. Duriez
RA-Letter (Proc. ICRA) 2017
This paper presents a physically-based algorithm to interactively simulate and control the motion of soft robots interacting with their environment. We use the Finite Element Method (FEM) to simulate the non-linear deformation of the soft structure, its actuators, and surroundings, and propose a control method relying on a quadratic optimization to find the inverse of the model. The novelty of this work is that the deformations due to contacts, including self-collisions, are taken into account in the optimization process. We propose a dedicated and efficient solver to handle the linear complementarity constraints introduced by the contacts. Thus, the method allows interactive transfer of the motion of soft robots from their task space to their actuator space while interacting with their surrounding. The method is generic and tested on several numerical examples and on a real cable-driven soft robot.
Real-time simulation of hydraulic components for interactive control of soft robots.
A. Rodrìguez, E. Coevoet, and C. Duriez
ICRA 2017
In this work we propose a new method for online motion planning in the task-space for hydraulic actuated soft robots. Our solution relies on the interactive resolution of an inverse kinematics problem, that takes into account the properties (mass, stiffness) of the deformable material used to build the robot. An accurate modeling of the mechanical behavior of hydraulic components is based on a novel GPU parallel method for the real-time computation of fluid weight distribution. The efficiency of the method is further increased by a novel GPU parallel leveraging mechanism. Our complete solution has been integrated within the open-source SOFA framework. In our results, we validate our simulation with a fabricated silicone cylinder and we demonstrate the usage of our approach for direct control of hydraulic soft robots.
Framework for online simulation of soft robots with optimization-based inverse model.
SIMPAR 2016 ★best paper award finalist
Soft robotics is an emerging field of robotics which requires computer-aided tools to simulate soft robots and provide models for their control. Until now, no unified software framework covering the different aspects exists. In this paper, we present such a framework from its theoretical foundations up to its implementation on top of SOFA, an open-source framework for deformable online simulation. The framework relies on continuum mechanics for modeling the robotic parts and boundary conditions like actuators or contacts using a unified representation based on Lagrange multipliers. It enables the digital robot to be simulated in its environment using a direct model. The model can also be inverted online using an optimization-based method which allows to control the physical robots in the task space. To demonstrate the effectiveness of the approach, we present various soft robots scenarios including ones where the robot is interacting with its environment. The software is freely available from https://project.inria.fr/softrobot/
Registration by interactive inverse simulation: application for adaptive radiotherapy.
E. Coevoet, N. Reynaert, L. Schiappacasse, J. Dequidt, and C. Duriez
IJCARS 2015
Purpose. This paper introduces a new methodology for semi-automatic registration of anatomical structure deformations. The contribution is to use an interactive inverse simulation of physics-based deformable model, computed in real-time.
Methods. The method relies on non-linear Finite Element Method (FEM) within a constraint-based framework. Given a set of few registered points provided by the user, a real-time optimization adapts the boundary conditions and(/or) some parameters of the FEM in order to obtain the adequate geometrical deformations. To dramatically fasten the process, the method relies on a projection of the model in the space of the optimization variables. In this reduced space, a quadratic programming problem is formulated and solved very quickly. The method is validated with numerical examples for retrieving some unknown parameters such as the Young’s modulus and some pressures on the boundaries of the model.
Results. The approach is employed it in the context of radiotherapy of the neck where weight loss during the 7 weeks of the therapy modifies the volume of the anatomical structures and induces large deformations. Indeed sensitive structures such as the parotid glands may cross the target volume due to these deformations which leads to adverse effects for the patient. We thus apply the approach for the registration of the parotid glands during the radiotherapy of the head and neck cancer.
Conclusions. The results show how the method could be used in a clinical routine and be employed in the planning in order to limit the radiations of these glands.
Vascular neurosurgery simulation with bimanual haptic feedback.
J. Dequidt, E. Coevoet, L. Thines, and C. Duriez
VRIPHYS 2015
Virtual surgical simulators face many computational challenges: they need to provide biophysical accuracy, realistic feed-backs and high-rate responses. Better biophysical accuracy and more realistic feed-backs (be they visual, haptic. . . ) induce more computational footprint. State-of-the-art approaches use high-performance hardware or find an acceptable trade-off between performance and accuracy to deliver interactive yet pedagogically relevant simulators. In this paper, we propose an interactive vascular neurosurgery simulator that provides bi-manual interaction with haptic feedback. The simulator is an original combination of states-of-the-art techniques that allows visual realism, bio-physical realism, complex interactions with the anatomical structures and the instruments and haptic feedback. Training exercises are also proposed to learn and to perform the different steps of intracranial aneurysm surgery (IAS). We assess the performance of our simulator with quantitative performance benchmarks and qualitative assessments of junior and senior clinicians.
Real-time control of soft-robots using asynchronous finite element modeling.
F. Largillière, V. Verona, E. Coevoet, J. Dequidt, and C. Duriez
ICRA 2015
Finite Element analysis can provide accurate deformable models for soft-robots. However, using such models is very difficult in a real-time system of control. In this paper, we introduce a generic solution that enables a high-rate control and that is compatible with strong real-time constraints. From a Finite Element analysis, computed at low rate, an inverse model of the robot outputs the setpoint values for the actuator in order to obtain a desired trajectory. This inverse problem uses a QP (quadratic-programming) algorithm based on the equations set by the Finite Element Method. To improve the update rate performances, we propose an asynchronous simulation framework that provides a better trade-off between the deformation accuracy and the computational burden. Complex computations such as accurate FEM deformations are done at low frequency while the control is performed at high frequency with strong real-time constraints. The two simulation loops (high frequency and low frequency loops) are mechanically coupled in order to guarantee mechanical accuracy of the system over time. Finally, the validity of the multi-rate simulation is discussed based on measurements of the evolution in the QP matrix and an experimental validation is conducted to validate the correctness of the high-rate inverse model on a real robot.
Introducing interactive inverse FEM simulation and its application for adaptive radiotherapy.
E. Coevoet, N. Reynaert, L. Schiappacasse, J. Dequidt, and C. Duriez
MICCAI 2014
We introduce a new methodology for semi-automatic deformable registration of anatomical structures, using interactive inverse simulations. The method relies on non-linear real-time Finite Element Method (FEM) within a constraint-based framework. Given a set of few registered points provided by the user, a real-time optimization adapts the boundary conditions and(/or) some parameters of the FEM in order to obtain the adequate geometrical deformations. To dramatically fasten the process, the method relies on a projection of the model in the space of the optimization variables. In this reduced space, a quadratic programming problem is formulated and solved very quickly. The method is validated with numerical examples for retrieving Young’s modulus and some pressures on the boundaries. Then, we apply the approach for the registration of the parotid glands during the radiotherapy of the head and neck cancer. Radiotherapy treatment induces weight loss that modifies the shape and the positions of these structures and they eventually intersect the target volume. We show how we could adapt the planning to limit the radiation of these glands.
