2,952 research outputs found

    Decentralized Trajectory Tracking Control for Soft Robots Interacting With the Environment

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    Despite the classic nature of the problem, trajectory tracking for soft robots, i.e., robots with compliant elements deliberately introduced in their design, still presents several challenges. One of these is to design controllers which can obtain sufficiently high performance while preserving the physical characteristics intrinsic to soft robots. Indeed, classic control schemes using high-gain feedback actions fundamentally alter the natural compliance of soft robots effectively stiffening them, thus de facto defeating their main design purpose. As an alternative approach, we consider here using a low-gain feedback, while exploiting feedforward components. In order to cope with the complexity and uncertainty of the dynamics, we adopt a decentralized, iteratively learned feedforward action, combined with a locally optimal feedback control. The relative authority of the feedback and feedforward control actions adapts with the degree of uncertainty of the learned component. The effectiveness of the method is experimentally verified on several robotic structures and working conditions, including unexpected interactions with the environment, where preservation of softness is critical for safety and robustness

    Operational space control of a lightweight robotic arm actuated by shape memory alloy wires: a comparative study.

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    This article presents the design and control of a two-link lightweight robotic arm using shape memory alloy wires as actuators. Both a single-wire actuated system and an antagonistic configuration system are tested in open and closed loops. The mathematical model of the shape memory alloy wire, as well as the kinematics and dynamics of the robotic arm, are presented. The operational space control of the robotic arm is performed using a joint space control in the inner loop and closed-loop inverse kinematics in the outer loop. In order to choose the best joint space control approach, a comparative study of four different control approaches (proportional derivative, sliding mode, adaptive, and adaptive sliding mode control) is carried out for the proposed model. From this comparative analysis, the adaptive controller was chosen to perform operational space control. This control helps us to perform accurate positioning of the end-effector of shape memory alloy wire–based robotic arm. The complete operational space control was successfully tested through simulation studies performing position reference tracking in the end-effector space. Through simulation studies, the proposed control solution is successfully verified to control the hysteretic robotic arm

    The AFLOW Fleet for Materials Discovery

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    The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data driven research. With the intent to accelerate the development and the deployment of new technologies, the AFLOW Fleet for computational materials design automates high-throughput first principles calculations, and provides tools for data verification and dissemination for a broad community of users. AFLOW incorporates different computational modules to robustly determine thermodynamic stability, electronic band structures, vibrational dispersions, thermo-mechanical properties and more. The AFLOW data repository is publicly accessible online at aflow.org, with more than 1.7 million materials entries and a panoply of queryable computed properties. Tools to programmatically search and process the data, as well as to perform online machine learning predictions, are also available.Comment: 14 pages, 8 figure

    Reliability-based design optimization using kriging surrogates and subset simulation

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    The aim of the present paper is to develop a strategy for solving reliability-based design optimization (RBDO) problems that remains applicable when the performance models are expensive to evaluate. Starting with the premise that simulation-based approaches are not affordable for such problems, and that the most-probable-failure-point-based approaches do not permit to quantify the error on the estimation of the failure probability, an approach based on both metamodels and advanced simulation techniques is explored. The kriging metamodeling technique is chosen in order to surrogate the performance functions because it allows one to genuinely quantify the surrogate error. The surrogate error onto the limit-state surfaces is propagated to the failure probabilities estimates in order to provide an empirical error measure. This error is then sequentially reduced by means of a population-based adaptive refinement technique until the kriging surrogates are accurate enough for reliability analysis. This original refinement strategy makes it possible to add several observations in the design of experiments at the same time. Reliability and reliability sensitivity analyses are performed by means of the subset simulation technique for the sake of numerical efficiency. The adaptive surrogate-based strategy for reliability estimation is finally involved into a classical gradient-based optimization algorithm in order to solve the RBDO problem. The kriging surrogates are built in a so-called augmented reliability space thus making them reusable from one nested RBDO iteration to the other. The strategy is compared to other approaches available in the literature on three academic examples in the field of structural mechanics.Comment: 20 pages, 6 figures, 5 tables. Preprint submitted to Springer-Verla

    Governing equations of tissue modelling and remodelling: A unified generalised description of surface and bulk balance

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    Several biological tissues undergo changes in their geometry and in their bulk material properties by modelling and remodelling processes. Modelling synthesises tissue in some regions and removes tissue in others. Remodelling overwrites old tissue material properties with newly formed, immature tissue properties. As a result, tissues are made up of different "patches", i.e., adjacent tissue regions of different ages and different material properties, within evolving boundaries. In this paper, generalised equations governing the spatio-temporal evolution of such tissues are developed within the continuum model. These equations take into account nonconservative, discontinuous surface mass balance due to creation and destruction of material at moving interfaces, and bulk balance due to tissue maturation. These equations make it possible to model patchy tissue states and their evolution without explicitly maintaining a record of when/where resorption and formation processes occurred. The time evolution of spatially averaged tissue properties is derived systematically by integration. These spatially-averaged equations cannot be written in closed form as they retain traces that tissue destruction is localised at tissue boundaries. The formalism developed in this paper is applied to bone tissues, which exhibit strong material heterogeneities due to their slow mineralisation and remodelling processes. Evolution equations are proposed in particular for osteocyte density and bone mineral density. Effective average equations for bone mineral density (BMD) and tissue mineral density (TMD) are derived using a mean-field approximation. The error made by this approximation when remodelling patchy tissue is investigated. The specific time signatures of BMD or TMD during remodelling events may provide a way to detect these events occurring at lower, unseen spatial resolutions from microCT scans.Comment: 14 pages, 8 figures. V2: minor stylistic changes, more detailed derivation of Eqs (30)-(31), additional comments on implication of BMD and TMD signatures for microCT scan

    Towards a Modular Framework for Visco-Hyperelastic Simulations of Soft Material Manipulators with Well-Parameterised Material

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    Controller design for continuum robots maintains to be a difficult task. Testing controllers requires dedicated work in manufacturing and investment into hardware as well as software, to acquire a test bench capable of performing dynamic control tasks. Typically, proprietary software for practical controller design such as Matlab/Simulink is used but lacks specific implementations of soft material robots. This intermediate work presents the results of a toolchain to derive well-identified rod simulations. State-of-the-art methods to simulate the dynamics of continuum robots are integrated into an object-oriented implementation and wrapped into the Simulink framework. The generated S-function is capable of handling arbitrary, user-defined input such as pressure actuation or external tip forces as demonstrated in numerical examples. With application to a soft pneumatic actuator, stiffness parameters of a nonlinear hyperelastic material law are identified via finite element simulation and paired with heuristically identified damping parameters to perform dynamic simulation. To prove the general functionality of the simulation, a numerical example as well as a benchmark from literature is implemented and shown. A soft pneumatic actuator is used to generate validation data, which is in good accordance with the respective simulation output. The tool is provided as an open-source project. Code is available under https://gitlab.com/soft_material_robotics/cosserat-rod-simulink-sfunction.© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

    The infinite-range quantum random Heisenberg magnet

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    We study with exact diagonalization techniques the Heisenberg model for a system of SU(2) spins with S=1/2 and random infinite-range exchange interactions. We calculate the critical temperature T_g for the spin-glass to paramagnetic transition. We obtain T_g ~ 0.13, in good agreement with previous quantum Monte Carlo and analytical estimates. We provide a detailed picture for the different kind of excitations which intervene in the dynamical response chi''(w,T) at T=0 and analyze their evolution as T increases. We also calculate the specific heat Cv(T). We find that it displays a smooth maximum at TM ~ 0.25, in good qualitative agreement with experiments. We argue that the fact that TM>Tg is due to a quantum disorder effect.Comment: 17 pages, 14 figure
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