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

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

Trajectory Tracking Control Design for Large-Scale Linear Dynamical Systems With Applications to Soft Robotics

International audienceThis article presents new results to control process modeled through linear large-scale systems. Numerical methods are widely used to model physical systems, and the finite-element method is one of the most common methods. However, for this method to be precise, it requires a precise spatial mesh of the process. Large-scale dynamical systems arise from this spatial discretization. We propose a methodology to design an observer-based output feedback controller. First, a model reduction step is used to get a system of acceptable dimension. Based on this low-order system, two linear matrix inequality problems provide us, respectively, with the observer and controller gains. In both the cases, model and reduction errors are taken into account in the computations. This provides robustness with respect to the reduction step and guarantees the stability of the original large-scale system. Finally, the proposed method is applied to a physical setup-a soft robotics platform-to show its feasibility

Model Based Control of Soft Robots: A Survey of the State of the Art and Open Challenges

Continuum soft robots are mechanical systems entirely made of continuously deformable elements. This design solution aims to bring robots closer to invertebrate animals and soft appendices of vertebrate animals (e.g., an elephant's trunk, a monkey's tail). This work aims to introduce the control theorist perspective to this novel development in robotics. We aim to remove the barriers to entry into this field by presenting existing results and future challenges using a unified language and within a coherent framework. Indeed, the main difficulty in entering this field is the wide variability of terminology and scientific backgrounds, making it quite hard to acquire a comprehensive view on the topic. Another limiting factor is that it is not obvious where to draw a clear line between the limitations imposed by the technology not being mature yet and the challenges intrinsic to this class of robots. In this work, we argue that the intrinsic effects are the continuum or multi-body dynamics, the presence of a non-negligible elastic potential field, and the variability in sensing and actuation strategies.Comment: 69 pages, 13 figure

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

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