Simulation Study of the Upper-limb Wrench Feasible Set with Glenohumeral Joint Constraints

The aim of this work is to improve musculoskeletal-based models of the upper-limb Wrench Feasible Set i.e. the set of achievable maximal wrenches at the hand for applications in collaborative robotics and computer aided ergonomics. In particular, a recent method performing wrench capacity evaluation called the Iterative Convex Hull Method is upgraded in order to integrate non dislocation and compression limitation constraints at the glenohumeral joint not taken into account in the available models. Their effects on the amplitude of the force capacities at the hand, glenohumeral joint reaction forces and upper-limb muscles coordination in comparison to the original iterative convex hull method are investigated in silico. The results highlight the glenohumeral potential dislocation for the majority of elements of the wrench feasible set with the original Iterative Convex Hull method and the fact that the modifications satisfy correctly stability constraints at the glenohumeral joint. Also, the induced muscles coordination pattern favors the action of stabilizing muscles, in particular the rotator-cuff muscles, and lowers that of known potential destabilizing ones according to the literature.Comment: 30 pages (double spacing), 10 figures, 2 table

Upper-Limb Isometric Force Feasible Set: Evaluation of Joint Torque-Based Models

International audienceA force capacity evaluation for a given posture may provide better understanding of human motor abilities for applications in sport sciences, rehabilitation and ergonomics. From data on posture and maximum isometric joint torques, the upper-limb force feasible set of the hand was predicted by four models called force ellipsoid, scaled force ellipsoid, force polytope and scaled force polytope, which were compared with a measured force polytope. The volume, shape and force prediction errors were assessed. The scaled ellipsoid underestimated the maximal mean force, and the scaled polytope overestimated it. The scaled force ellipsoid underestimated the volume of the measured force distribution, whereas that of the scaled polytope was not significantly different from the measured distribution but exhibited larger variability. All the models characterized well the elongated shape of the measured force distribution. The angles between the main axes of the modelled ellipsoids and polytopes and that of the measured polytope were compared. The values ranged from 7.3° to 14.3°. Over the entire surface of the force ellipsoid, 39.7% of the points had prediction errors less than 50 N; 33.6% had errors between 50 and 100 N; and 26.8% had errors greater than 100N. For the force polytope, the percentages were 56.2%, 28.3% and 15.4%, respectively

Efficient calculation of human wrench capacity based on human musculoskeletal models Application in collaborative robot control

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Common wrench capability evaluation of a human-robot collaborative system

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On-line feasible wrench polytope evaluation based on human musculoskeletal models: an iterative convex hull method

© 2020 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 works.International audienceMany recent human-robot collaboration strategies, such as Assist-As-Needed (AAN), are promoting humancentered robot control, where the robot continuously adapts its assistance level based on the real-time need of its human counterpart. One of the fundamental assumptions of these approaches is the ability to measure or estimate the physical capacity of humans in real-time. In this work, we propose an algorithm for the feasibility set analysis of a generic class of linear algebra problems. This novel iterative convex-hull method is applied to the determination of the feasible Cartesian wrench polytope associated to a musculoskeletal model of the human upper limb. The method is capable of running in real-time and allows the user to define the desired estimation accuracy. The algorithm performance analysis shows that the execution time has near-linear relationship to the considered number of muscles, as opposed to the exponential relationship of the conventional methods. Finally, real-time robot control application of the algorithm is demonstrated in a Collaborative carrying experiment, where a human operator and a Franka Emika Panda robot jointly carry a 7kg object. The robot is controlled in accordance to the AAN paradigm maintaining the load carried by the human operator at 30% of its carrying capacity

Redundancy Tubes: Modelling Individual and Group Range-of-Motions Along a Path

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Analyse biomécanique et simulation du mouvement de préhension : application aux mouvements altérés

Prehension and upper-limb movements are of paramount importance in the repertoire of goal directed movements. As such, they are associated to a wide range of applications in biomechanics, rehabilitation, computer assisted ergonomics, robotics or animation. Moreover, their study and simulation in different populations such as young, middle aged, and elderly people or persons that suffer from a pathology allow to gain insight into human movement control and motor redundancy. The presented researches concern both fields. More precisely the tools of biomechanics, robotics and neural networks have been used to:•Propose human movement and posture simulation tools based on motor control principles that integrate learning and intra-individual variability,•Better understand the human motricity and coordination of able bodied subjects as well as persons with a motor deficiency. The methodology is based on the use global biomechanical indices that characterize the whole upper-limb degrees of freedom implication.La préhension et les mouvements du membre supérieur occupent une place de choix dans le répertoire des mouvements intentionnels dirigés vers un but. De ce fait, ils sont associés à un champ d’applications très important dans les domaines de la biomécanique, de la rééducation, de l’ergonomie assistée par ordinateur, de la robotique ou de l’animation. Aussi, leur étude et leur simulation chez le sujet jeune, adulte, âgé, valide ou atteint d’une déficience motrice permet d’apporter des éléments de réponse à des questions scientifiques importantes concernant le contrôle du mouvement et notamment la gestion de la redondance motrice par le système nerveux central (SNC). C’est dans ce double contexte applicatif et plus fondamental que se situent les travaux décrits dans ce mémoire. Plus précisément, notre démarche a consisté à exploiter les outils de modélisation de la biomécanique, de la robotique et des réseaux de neurones, afin de développer des outils et méthodologies pour :•la proposition d’outils de simulation du mouvement humain basés sur les principes de contrôle par le SNC intégrant notamment la notion d’apprentissage et de variabilité intra-individuelle.•Une meilleure compréhension de la motricité humaine et de la coordination motrice par le SNC chez des sujets valides ou atteints de pathologies par la quantification d’indices biomécaniques globaux caractérisant l’utilisation de l’ensemble des degrés de liberté des segments du membre supérieur. Ces indices peuvent conduire à une meilleure évaluation de la motricité de patients et ainsi contribuer à l’amélioration des protocoles de rééducation ainsi qu’à l’optimisation du mouvement ou de l’environnement dans le cadre d’applications en ergonomie

MODELISATION DYNAMIQUE DU MOUVEMENT DE PREHENSION (ASSISTANCE A LA MANIPULATION EN MILIEU ENCOMBRE)

ORSAY-PARIS 11-BU Sciences (914712101) / SudocSudocFranceF

Algorithmes génétiques pour prédire des polytopes de force

National audienceKnowledge of human’s force capacities enables the design of physical Human-Robot Interaction (pHRI) workspaces. As measuring force capacities for all postures is time consuming, predicting force capacities from a subset of measurements performed in a limited number of postures is crucial. The force capacities can be described as a convex polytope by means of a personalized musculoskeletal (MSK) model (Skuric et al. 2022). However, the tuning of a MSK model is difficult due to the high number of parameters. Thanks to its constraint-free nature on the optimization function, a genetic algorithm is implemented to find a MSK model parameter set, which fits and predicts force polytopes