Dynamic Control of Soft Robots

International audienceSoft robots present several advantages. However, one of the main challenges of this new field of robotics is to control these robots. The methods used to control rigid robots are not directly relevant and new approaches have to be invented or updated to be applied to this kind of robots. This paper introduces control solutions for soft robots studies taking into account dynamics of the system

SOFT ROBOT POSITIONING USING ARTIFICIAL NEURAL NETWORK

The experiment investigated the performance of an artificial neural network in solving the inverse kinematic problem of a soft robot. For this purpose, a simple soft robot was designed of building blocks, stringed on three rubber hoses, and an actuating system, to provide the hydraulic pressure. An axial extending of a hose, while the others are in the relaxed state, results in bending of the robot. The network was employed, as a black box, to approximate the behavior of the system. In accordance with the purpose, the input consisted of the desired spatial coordinates and the output of the step motor angular displacements. The network was trained and tested using records collected at 200 randomly chosen robot positions. The relative testing error of positioning, about 5%, confirmed a predictable robot behavior. The solution proposed is competitive in terms of simplicity, safety and price of realization. The experiment provided basics for the future research of the design of modular soft robots

Reduced Order Control of Soft Robots with Guaranteed Stability

International audienceThis work offers the ability to design a closed-loop strategy to control the dynamics of soft robots. A numericalmodel of a robot is obtained using the Finite Element Method,which leads to work with large-scale systems that are difficult tocontrol. The main contribution is a reduced order model-basedcontrol law, that consists in two main features: a reduced statefeedback tunes the performance while a Lyapunov functionguarantees the stability of the large-scale closed-loop systems.The method is generic and usable for any soft robot, as long asa FEM model is obtained. Simulation results show that we cancontrol and reduce the settling time of the soft robot and makeit converge faster without oscillations to a desired position

Visual Servoing Control of Soft Robots based on Finite Element Model

International audienceIn this paper, we propose a strategy for the control of soft robots with visual tracking and simulation-based predictor. A kinematic model of soft robots is obtained thanks to the Finite Element Method (FEM) computed in real-time. The FEM allows to obtain a prediction of the Jacobian matrix of the robot. This allows a first control of the robot, in the actuator space. Then, a second control strategy based on the feedback of infrared cameras is developed to obtain a correction of the effector position. The robust stability of this closed-loop system is obtained based on Lyapunov stability theory. Otherwise, to deal with the problem of image features (the marker points placed on the end effector of soft robot) loss, a switched control strategy is proposed to combine both the open-loop controller and the closed-loop controller. Finally, experiments on a parallel soft robot driven by four cables are conducted and show the effectiveness of these methods for the real-time control of soft robots

Control Design for Soft Robots based on Reduced Order Model

International audienceInspired by nature, soft robots promise disruptive advances in robotics. Soft robots are naturally compliant and exhibit nonlinear behavior, which makes their study challenging. No unified framework exists to control these robots, especially when considering their dynamics. This work proposes a methodology to study this type of robots around a stable equilibrium point. It can make the robot converge faster and with reduced oscillations to a desired equilibrium state. Using computational mechanics, a large-scale dynamic model of the robot is obtained and model reduction algorithms enable the design of low order controller and observer. A real robot is used to demonstrate the interest of the results

Stiffness Control of Deformable Robots Using Finite Element Modeling

International audienceDue to the complexity of modeling deformable materials and infinite degrees of freedom, the rich background of rigid robot control has not been transferred to soft robots. Thus, most model-based control techniques developed for soft robots and soft haptic interfaces are specific to the particular device. In this paper, we develop a general method for stiffness control of soft robots suitable for arbitrary robot geometry and many types of actuation. Extending previous work that uses finite element modeling for position control, we determine the relationship between end-effector and actuator compliance, including the inherent device compliance, and use this to determine the appropriate controlled actuator stiffness for a desired stiffness of the end-effector. Such stiffness control, as the first component of impedance control, can be used to compensate for the natural stiffness of the deformable device and to control the robot's interaction with the environment or a user. We validate the stiffness projection on a deformable robot and include this stiffness projection in a haptic control loop to render a virtual fixture

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

Motion Control of Cable-Driven Continuum Catheter Robot through Contacts

International audienceCatheter-based intervention plays an important role in minimally invasive surgery. For the closed-loop control of catheter robot through contacts, the loss of contact sensing along the entire catheter might result in task failure. To deal with this problem, we propose a decoupled motion control strategy which allows to control insertion and bending independently. We model the catheter robot and the contacts using the Finite Element Method. Then, we combine the simulated system and the real system for the closed-loop motion control. The control inputs are computed by solving a quadratic programming (QP) problem with a linear complementarity problem (LCP). A simplified method is proposed to solve this optimization problem by converting it into a standard QP problem. Using the proposed strategy, not only the control inputs but also the contact forces along the entire catheter can be computed without using force sensors. Finally, we validate the proposed methods using both simulation and experiments on a cable-driven continuum catheter robot for the real-time motion control through contacts

Calibration and External Force Sensing for Soft Robots using an RGB-D Camera

International audienceBenefiting from the deformability of soft robots, calibration and force sensing for soft robots are possible using an external vision-based system, instead of embedded mechatronic force sensors. In this paper, we first propose a calibration method to calibrate both the sensor-robot coordinate system and the actuator inputs. This task is addressed through a sequential optimization problem for both variables. We also introduce an external force sensing system based on a real-time Finite Element (FE) model with the assumption of static configurations, and which consists of two steps: force location detection and force intensity computation. The algorithm that estimates force location relies on the segmentation of the point cloud acquired by an RGB-D camera. Then, the force intensities can be computed by solving an inverse quasi-static problem based on matching the FE model with the point cloud of the soft robot. As for validation, the proposed strategies for calibration and force sensing have been tested using a parallel soft robot driven by four cables

Vision-Based Sensing of External Forces Acting on Soft Robots Using Finite Element Method

International audienceIn this paper, we propose a new framework of external force sensing for soft robots based on the fusion of vision-based measurements and Finite Element Model (FEM) techniques. A precise mechanical model of the robot is built using real-time FEM to describe the relationship between the external forces acting on the robot and the displacement of predefined feature points. The position of these feature points on the real robot is measured using a vision system and is compared with the equivalent feature points in the finite element model. Using the compared displacement, the intensities of the external forces are computed by solving an inverse problem. Based on the developed FEM equations, we show that not only the intensities but also the locations of the external forces can be estimated. A strategy is proposed to find the correct locations of external forces among several possible ones. The method is verified and validated using both simulation and experiments on a soft sheet and a parallel soft robot (both of them have non-trivial shapes). The good results obtained from the experimental study demonstrate the capability of our approach