14 research outputs found

    Open-loop position control in collaborative, modular Variable-Stiffness-Link (VSL) robots

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    — Collaborative robots (cobots) open up new avenues in the fields of industrial robotics and physical Human-Robot Interaction (pHRI) as they are suitable to work in close approximation and in collaboration with humans. The integration and control of variable stiffness elements allow inherently safe interaction. Apart from notable work on Variable Stiffness Actuators, the concept of Variable-Stiffness-Link (VSL) manipulators promises safety improvements in cases of unintentional physical collisions. However, position control of these type of robotic manipulators is challenging for critical task-oriented motions (e.g., pick and place). Hence, the study of open-loop position control for VSL robots is crucial to achieve high levels of safety, accuracy and hardware cost-efficiency in pHRI applications. In this paper, we propose a hybrid, learning based kinematic modelling approach to improve the performance of traditional open-loop position controllers for a modular, collaborative VSL robot. We show that our approach improves the performance of traditional open-loop position controllers for robots with VSL and compensates for position errors, in particular, for lower stiffness values inside the links: Using our upgraded and modular robot, two experiments have been carried out to evaluate the behaviour of the robot during taskoriented motions. Results show that traditional model-based kinematics are not able to accurately control the position of the end-effector: the position error increases with higher loads and lower pressures inside the VSLs. On the other hand, we demonstrate that, using our approach, the VSL robot can outperform the position control compared to a robotic manipulator with 3D printed rigid links

    Natural History of MYH7-Related Dilated Cardiomyopathy

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    BACKGROUND: Variants in myosin heavy chain 7 (MYH7) are responsible for disease in 1% to 5% of patients with dilated cardiomyopathy (DCM); however, the clinical characteristics and natural history of MYH7-related DCM are poorly described. OBJECTIVE: We sought to determine the phenotype and prognosis of MYH7-related DCM. We also evaluated the influence of variant location on phenotypic expression. METHODS: We studied clinical data from 147 individuals with DCM-causing MYH7 variants (47.6% female; 35.6 ± 19.2 years) recruited from 29 international centers. RESULTS: At initial evaluation, 106 (72.1%) patients had DCM (left ventricular ejection fraction: 34.5% ± 11.7%). Median follow-up was 4.5 years (IQR: 1.7-8.0 years), and 23.7% of carriers who were initially phenotype-negative developed DCM. Phenotypic expression by 40 and 60 years was 46% and 88%, respectively, with 18 patients (16%) first diagnosed at <18 years of age. Thirty-six percent of patients with DCM met imaging criteria for LV noncompaction. During follow-up, 28% showed left ventricular reverse remodeling. Incidence of adverse cardiac events among patients with DCM at 5 years was 11.6%, with 5 (4.6%) deaths caused by end-stage heart failure (ESHF) and 5 patients (4.6%) requiring heart transplantation. The major ventricular arrhythmia rate was low (1.0% and 2.1% at 5 years in patients with DCM and in those with LVEF of ≤35%, respectively). ESHF and major ventricular arrhythmia were significantly lower compared with LMNA-related DCM and similar to DCM caused by TTN truncating variants. CONCLUSIONS: MYH7-related DCM is characterized by early age of onset, high phenotypic expression, low left ventricular reverse remodeling, and frequent progression to ESHF. Heart failure complications predominate over ventricular arrhythmias, which are rare

    A Hybrid Learning and Optimization Framework to Achieve Physically Interactive Tasks With Mobile Manipulators

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    This letter proposes a hybrid learning and optimization framework for mobile manipulators for complex and physically interactive tasks. The framework exploits an admittance-type physical interface to obtain intuitive and simplified human demonstrations and Gaussian Mixture Model (GMM)/Gaussian Mixture Regression (GMR) to encode and generate the learned task requirements in terms of position, velocity, and force profiles. Next, using the desired trajectories and force profiles generated by GMM/GMR, the impedance parameters of a Cartesian impedance controller are optimized online through a Quadratic Program augmented with an energy tank to ensure the passivity of the controlled system. Two experiments are conducted to validate the framework, comparing our method with two approaches with constant stiffness (high and low). The results showed that the proposed method outperforms the other two cases in terms of trajectory tracking and generated interaction forces, even in the presence of disturbances such as unexpected end-effector collisions

    A Personalizable Controller for the Walking Assistive omNi-Directional Exo-Robot (WANDER)

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    Preserving and encouraging mobility in the elderly and adults with chronic conditions is of paramount importance. However, existing walking aids are either inadequate to provide sufficient support to users' stability or too bulky and poorly maneuverable to be used outside hospital environments. In addition, they all lack adaptability to individual requirements. To address these challenges, this paper introduces WANDER, a novel Walking Assistive omNi-Directional Exo-Robot. It consists of an omnidirectional platform and a robust aluminum structure mounted on top of it, which provides partial body weight support. A comfortable and minimally restrictive coupling interface embedded with a force/torque sensor allows to detect users' intentions, which are translated into command velocities by means of a variable admittance controller. An optimization technique based on users' preferences, i.e., Preference-Based Optimization (PBO) guides the choice of the admittance parameters (i.e., virtual mass and damping) to better fit subject-specific needs and characteristics. Experiments with twelve healthy subjects exhibited a significant decrease in energy consumption and jerk when using WANDER with PBO parameters as well as improved user performance and comfort. The great interpersonal variability in the optimized parameters highlights the importance of personalized control settings when walking with an assistive device, aiming to enhance users' comfort and mobility while ensuring reliable physical support

    Project Summary: TRUST-ROB, Towards Resilient UGV and UAV Manipulator Teams For Robotic Search and Rescue Tasks

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    The paper was presented at the Project Summary sessions.This Project Summary paper reviews the main contributions and lessons learned from the TRUST-ROB project: “Towards Resilient UGV and UAV Manipulator Teams for Robotic Search and Rescue Tasks”, which has been developed between 2019 and 2022 with funding from the Spanish Government (RTI2018-093421-B-I00).This TRUST-ROB project has been funded by the Ministerio de Ciencia, Innovación y Universidades, Gobierno de España RTI2018-093421-B-I00. The presentation of this Project Summary paper has been partially funded by Universidad de Málaga, Andalucía Tech
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