Enhancing Human-Robot Collaboration Transportation through Obstacle-Aware Vibrotactile Feedback

Transporting large and heavy objects can benefit from Human-Robot Collaboration (HRC), increasing the contribution of robots to our daily tasks and reducing the risk of injuries to the human operator. This approach usually posits the human collaborator as the leader, while the robot has the follower role. Hence, it is essential for the leader to be aware of the environmental situation. However, when transporting a large object, the operator's situational awareness can be compromised as the object may occlude different parts of the environment. This paper proposes a novel haptic-based environmental awareness module for a collaborative transportation framework that informs the human operator about surrounding obstacles. The robot uses two LIDARs to detect the obstacles in the surroundings. The warning module alerts the operator through a haptic belt with four vibrotactile devices that provide feedback about the location and proximity of the obstacles. By enhancing the operator's awareness of the surroundings, the proposed module improves the safety of the human-robot team in co-carrying scenarios by preventing collisions. Experiments with two non-expert subjects in two different situations are conducted. The results show that the human partner can successfully lead the co-transportation system in an unknown environment with hidden obstacles thanks to the haptic feedback.Comment: 6 pages, 5 figures, for associated video, see this https://youtu.be/UABeGPIIrH

Markerless 3D human pose tracking through multiple cameras and AI: Enabling high accuracy, robustness, and real-time performance

Tracking 3D human motion in real-time is crucial for numerous applications across many fields. Traditional approaches involve attaching artificial fiducial objects or sensors to the body, limiting their usability and comfort-of-use and consequently narrowing their application fields. Recent advances in Artificial Intelligence (AI) have allowed for markerless solutions. However, most of these methods operate in 2D, while those providing 3D solutions compromise accuracy and real-time performance. To address this challenge and unlock the potential of visual pose estimation methods in real-world scenarios, we propose a markerless framework that combines multi-camera views and 2D AI-based pose estimation methods to track 3D human motion. Our approach integrates a Weighted Least Square (WLS) algorithm that computes 3D human motion from multiple 2D pose estimations provided by an AI-driven method. The method is integrated within the Open-VICO framework allowing simulation and real-world execution. Several experiments have been conducted, which have shown high accuracy and real-time performance, demonstrating the high level of readiness for real-world applications and the potential to revolutionize human motion capture.Comment: 19 pages, 7 figure

A Self-Tuning Impedance-based Interaction Planner for Robotic Haptic Exploration

This paper presents a novel interaction planning method that exploits impedance tuning techniques in response to environmental uncertainties and unpredictable conditions using haptic information only. The proposed algorithm plans the robot's trajectory based on the haptic interaction with the environment and adapts planning strategies as needed. Two approaches are considered: Exploration and Bouncing strategies. The Exploration strategy takes the actual motion of the robot into account in planning, while the Bouncing strategy exploits the forces and the motion vector of the robot. Moreover, self-tuning impedance is performed according to the planned trajectory to ensure compliant contact and low contact forces. In order to show the performance of the proposed methodology, two experiments with a torque-controller robotic arm are carried out. The first considers a maze exploration without obstacles, whereas the second includes obstacles. The proposed method performance is analyzed and compared against previously proposed solutions in both cases. Experimental results demonstrate that: i) the robot can successfully plan its trajectory autonomously in the most feasible direction according to the interaction with the environment, and ii) a compliant interaction with an unknown environment despite the uncertainties is achieved. Finally, a scalability demonstration is carried out to show the potential of the proposed method under multiple scenarios.Comment: 8 pages, 9 figures, accepted for IEEE Robotics and Automation Letters (RA-L) and IEEE/RSJ International Conference on Intelligent Robots and Systems 202

Robot-Assisted Navigation for Visually Impaired through Adaptive Impedance and Path Planning

This paper presents a framework to navigate visually impaired people through unfamiliar environments by means of a mobile manipulator. The Human-Robot system consists of three key components: a mobile base, a robotic arm, and the human subject who gets guided by the robotic arm via physically coupling their hand with the cobot's end-effector. These components, receiving a goal from the user, traverse a collision-free set of waypoints in a coordinated manner, while avoiding static and dynamic obstacles through an obstacle avoidance unit and a novel human guidance planner. With this aim, we also present a legs tracking algorithm that utilizes 2D LiDAR sensors integrated into the mobile base to monitor the human pose. Additionally, we introduce an adaptive pulling planner responsible for guiding the individual back to the intended path if they veer off course. This is achieved by establishing a target arm end-effector position and dynamically adjusting the impedance parameters in real-time through a impedance tuning unit. To validate the framework we present a set of experiments both in laboratory settings with 12 healthy blindfolded subjects and a proof-of-concept demonstration in a real-world scenario.Comment: 7 pages, 7 figures, submitted to IEEE International Conference on Robotics and Automation, for associated video, see https://youtu.be/B94n3QjdnJ

Cinemática y prototipado de un manipulador paralelo con centro de rotación remoto para robótica quirúrgica

[Resumen] En este artículo se presenta el modelo cinemático de un robot paralelo y la construcción de un prototipo de dos grados de libertad, cuyo objeto es servir como posicionador de instrumentos de cirugía laparoscópica. El robot tiene una configuración en paralelo, con estructura de mecanismo de cinco barras con ejes no paralelos, con dos articulaciones activas. La particularidad de este mecanismo reside en su forma no planar, es decir, los ejes de las articulaciones del robot no se encuentran en un mismo plano, sino que sus extensiones se cortan en un punto remoto, sobre el cual pivota el elemento terminal del manipulador. El espacio de trabajo de este prototipo en un casquete esférico con centro en el puerto de entrada en el paciente. Al no tratarse de un manipulador de cadena abierta, su cinemática es más compleja. En este trabajo se presenta el modelo cinemático inverso para control en coordenadas esféricas, y su validación mediante la construcción de un prototipo

Uso del haptic paddle con aprendizaje basado en proyectos

[Resumen] En este trabajo se presenta la experiencia de la utilización docente de un dispositivos háptico desarrollado como una nueva versión del haptic paddle, creado en la Universidad de Stanford a mediados de los 90. Se trata de un dispositivo educativo de bajo coste y simple que puede ser ensamblado y programado por los estudiantes, y que se usó para enseñanza de dinámica de sistemas. El diseño realizado usa una electrónica completamente off the shelf, rodamientos y tornillería métrica estándar y piezas fabricadas mediante impresión 3D. En este trabajo se presenta este dispositivo junto con la experiencia de su utilización docente, mediante aprendizaje basado en proyectos, en una asignatura de máster de ingeniería mecatrónica. Se trata de la primera experiencia con un total de ocho kits de haptic paddle en la asignatura de Teleoperación y Telerrobótica, junto con aprendizaje basado en proyectos (ABP) y el uso de lenguajes de modelado. Se describen la organización y el desarrollo de las sesiones de prácticas con conclusiones sobre la adecuación del los dispositivos y métodos utilizados.Universidad de Málaga; PIE 15-18

Upper-Limb Kinematic Parameter Estimation and Localization Using a Compliant Robotic Manipulator

Assistive and rehabilitation robotics have gained momentum over the past decade and are expected to progress significantly in the coming years. Although relevant and promising research advances have contributed to these fields, challenges regarding intentional physical contact with humans remain. Despite being a fundamental component of assistive and rehabilitation tasks, there is an evident lack of work related to robotic manipulators that intentionally manipulate human body parts. Moreover, existing solutions involving end-effector robots are not based on accurate knowledge of human limb dimensions and their current configuration. This knowledge, which is essential for safe human–limb manipulation, depends on the grasping location and human kinematic parameters. This paper addresses the upper-limb manipulation challenge and proposes a pose estimation method using a compliant robotic manipulator. To the best of our knowledge, this is the first attempt to address this challenge. A kinesthetic-based approach enables estimation of the kinematic parameters of the human arm without integrating external sensors. The estimation method relies only on proprioceptive data obtained from a collaborative robot with a Cartesian impedance-based controller to follow a compliant trajectory that depends on human arm kinodynamics. The human arm model is a 2-degree of freedom (DoF) kinematic chain. Thus, prior knowledge of the arm's behavior and an estimation method enables estimation of the kinematic parameters. Two estimation methods are implemented and compared: i) Hough transform (HT); ii) least squares (LS). Furthermore, a resizable, sensorized dummy arm is designed for experimental validation of the proposed approach. Outcomes from six experiments with different arm lengths demonstrate the repeatability and effectiveness of the proposed methodology, which can be used in several rehabilitation robotic applications

The COMT Val158 Met polymorphism as an associated risk factor for Alzheimer disease and mild cognitive impairment in APOE 4 carriers

<p>Abstract</p> <p>Background</p> <p>The aim of this study is to examine the influence of the <it>catechol-O-methyltranferase (COMT) </it>gene (polymorphism Val158 Met) as a risk factor for Alzheimer's disease (AD) and mild cognitive impairment of amnesic type (MCI), and its synergistic effect with the <it>apolipoprotein E gene (APOE)</it>.</p> <p>A total of 223 MCI patients, 345 AD and 253 healthy controls were analyzed. Clinical criteria and neuropsychological tests were used to establish diagnostic groups.</p> <p>The DNA Bank of the University of the Basque Country (UPV-EHU) (Spain) determined <it>COMT </it>Val158 Met and <it>APOE </it>genotypes using real time polymerase chain reaction (rtPCR) and polymerase chain reaction (PCR), and restriction fragment length polymorphism (RFLPs), respectively. Multinomial logistic regression models were used to determine the risk of AD and MCI.</p> <p>Results</p> <p>Neither <it>COMT </it>alleles nor genotypes were independent risk factors for AD or MCI. The high activity genotypes (GG and AG) showed a synergistic effect with <it>APOE ε4 </it>allele, increasing the risk of AD (OR = 5.96, 95%CI 2.74-12.94, p < 0.001 and OR = 6.71, 95%CI 3.36-13.41, p < 0.001 respectivily). In AD patients this effect was greater in women.</p> <p>In MCI patients such as synergistic effect was only found between AG and <it>APOE ε4 </it>allele (OR = 3.21 95%CI 1.56-6.63, p = 0.02) and was greater in men (OR = 5.88 95%CI 1.69-20.42, p < 0.01).</p> <p>Conclusion</p> <p><it>COMT </it>(Val158 Met) polymorphism is not an independent risk factor for AD or MCI, but shows a synergistic effect with <it>APOE ε4 </it>allele that proves greater in women with AD.</p

Natural History of MYH7-Related Dilated Cardiomyopathy

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. OBJECTIVES 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. (C) 2022 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation