Control of Elastic Soft Robots based on Real-Time Finite Element Method

International audienceIn this paper, we present a new method for the control of soft robots with elastic behavior, piloted by several actuators. The central contribution of this work is the use of the Finite Element Method (FEM), computed in real-time, in the control algorithm. The FEM based simulation computes the nonlinear deformations of the robots at interactive rates. The model is completed by Lagrange multipliers at the actuation zones and at the end-effector position. A reduced compliance matrix is built in order to deal with the necessary inversion of the model. Then, an iterative algorithm uses this compliance matrix to find the contribution of the actuators (force and/or position) that will deform the structure so that the terminal end of the robot follows a given position. Additional constraints, like rigid or deformable obstacles, or the internal characteristics of the actuators are integrated in the control algorithm. We illustrate our method using simulated examples of both serial and parallel structures and we validate it on a real 3D soft robot made of silicon

Real-time FEM based control of soft surgical robots

International audienceIn this paper, we present a new method for the control of soft surgical robots based on the real-time inverse simulation with internal deformation computed through the use of Finite Element Method. We also consider the coupling of this method with a modified version of the same algorithm for parametrization of soft-tissue models, in order to control the navigation of the robot while gathering information on the surrounding organs

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

Static kinematics for an antagonistically actuated robot based on a beam-mechanics-based model

Soft robotic structures might play a major role in the 4th industrial revolution. Researchers have successfully demonstrated advantages of soft robotics over traditional robots made of rigid links and joints in several application areas including manufacturing, healthcare and surgical interventions. However, soft robots have limited ability to exert higher forces when it comes to interaction with the environment, hence, change their stiffness on demand over a wide range. One stiffness mechanism embodies tendon-driven and pneumatic air actuation in an antagonistic way achieving variable stiffness values. In this paper, we apply a beammechanics-based model to this type of soft stiffness controllable robot. This mathematical model takes into account the various stiffness levels of the soft robotic manipulator as well as interaction forces with the environment at the tip of the manipulator. The analytical model is implemented into a robotic actuation system made of motorised linear rails with load cells (obtaining applied forces to the tendons) and a pressure regulator. Here, we present and analyse the performance and limitations of our model

Robust Fabrication of a Soft Mechanosensor based on Pneumatic Measurements

International audienceIn this extended abstract, we complement the work presented in a previous paper where we have shown the modeling of a novel soft pneumatic mechanosensor. With the objective of giving a demo at the RoboTac 2019 workshop, we discuss robust manufacturing techniques that enable us to fabricate such soft mechanosensors out of silicone with embedded cavities in a consistent manner