On geodesic paths and least-cost motions for human-like tasks

We are interested in ”human-like” automatic mo- tion generation. The apparent redundancy of the humanoid wrt its explicit tasks lead to the problem of choosing a plausible movement in the framework of redundant kinematics. Some results have been obtained in the human motion literature for reach motion that involves the position of the hands. We discuss these results and a motion generation scheme associated. When orientation is also explicitly required, very few works are available and even the methods for analysis are not defined. We discuss the choice for metrics adapted to the orientation, and also the problems encountered in defining a proper metric in both position and orientation. Motion capture and simulations are provided in both cases. The main goals of this paper are : - to provide a survey on human motion features at task level for both position and orientation, - to propose a kinematic control scheme based on these features - to define properly the error between motion capture and automatic motion simulation

Experimental Study on Human Arm Reaching with and without a Reduced Mobility for Applications in Medical Human-Interactive Robotics

Along with increasing advances in robotic technologies, there are now significant efforts under way to improve the quality of life especially those with physical disabilities or impairments. Control of such medical human-interactive robotics (HIR) involves complications in its design and control due to uncertain human factors. This dissertation makes its efforts to resolve three main challenges of an advanced HIR controller development: 1) detecting the operator’s motion intent, 2) understanding human motor behavior from the robotic perspective, and 3) generating reference motion for the HIR. Our interests in such challenges are limited to the point-to-point reaching of the human arm for applications of their solutions in the control of rehabilitation exoskeletons, therapeutic haptic devices, and prosthetic arms. In the context of human motion intent detection, a mobile motion capture system (MCS) enhanced with myoprocessors is developed to capture kinematics and dynamics of human arm in reaching movements. The developed MCS adopts wireless IMU (inertial measurement unit) sensors to capture ADL (activities of daily life) motions in the real-life environment. In addition, measured muscle activation patterns from selected muscle groups are converted into muscular force values by myoprocessors. This allows a reliable motion intent detection by quantify one of the most frequently used driving signal of the HIR, EMG (electromyography), in a standardized way. In order to understand the human motor behavior from the robotic viewpoint, a computational model on reaching is required. Since such model can be constituted by experimental observations, this dissertation look into invariant motion features of reaching with and without elbow constraint condition to establish a foundation of the computational model. The HIR should generate its reference motions by reflecting motor behavior of the natural human reaching. Though the accurate approximation of such behavior is critical, we also need to take into account the computational cost, especially for real-time applications such as the HIR control. In this manner, a higher order kinematic synthesis of mechanical linkage systems is adopted to approximate natural human hand profiles. Finally, a novel control concept of a myo-prosthetic arm is proposed as an application of all findings and efforts made in this dissertation

Analyse et simulation de mouvements d'atteinte contraints en position et orientation pour un humanoïde de synthèse

La simulation du geste humain est une thématique de recherche importante et trouve notamment une application dans l'analyse ergonomique pour l'aide à la conception de postes de travail. Le sujet de cette thèse concerne la génération automatique de tâches d'atteinte dans le plan horizontal pour un humanoïde. Ces dernières, à partir d'un objectif exprimé dans l'espace de la tâche, requièrent une coordination de l'ensemble des liaisons. L'une des principales difficultés rencontrées lors de la simulation de gestes réalistes est liée à la redondance naturelle de l'humain. Notre démarche est focalisée principalement sur deux aspects : - le mouvement de la main dans l'espace opérationnel (trajectoire spatiale et profil temporel), - la coordination des différentes sous-chaînes cinématiques. Afin de caractériser le mouvement humain, nous avons mené une campagne de capture de mouvements pour des gestes d'atteinte contraignant la position et l'orientation de la main dans le plan horizontal. Ces acquisitions nous ont permis de connaître l'évolution spatiale et temporelle de la main dans l'espace de la tâche, en translation et en rotation. Ces données acquises couplées à une méthode de rejeu ont également permis d'analyser les relations intrinsèques qui lient l'espace de la tâche à l'espace articulaire du mannequin. Le schéma de génération automatique de mouvements réalistes est basé sur une pile de tâche avec une approche cinématique. L'hypothèse retenue pour simuler le geste est de suivre le chemin le plus court dans l'espace de la tâche tout en bornant le coût dans l'espace articulaire. Un ensemble de paramètres permet de régler le schéma. Il en résulte une cartographie de réglages qui permet de simuler une classe de mouvements réalistes. Enfin, ce schéma de génération automatique de mouvements réalistes est validé par une comparaison quantitative et qualitative entre la simulation et le geste humain. ABSTRACT : The simulation of human movement is an active theme of research, particularly in ergonomic analysis to aid in the design of workstations. The aim of this thesis concerns the automatic generation of reaching tasks in the horizontal plane for a virtual humanoid. An objective expressed in the task space, requires coordination of all joints of the mannequin. The main difficulties encountered in the simulation of realistic movements is related to the natural redundancy of the human. Our approach is focused mainly on two aspects: - Motion of the hand's operator in the task space (spatial and temporal aspect), - Coordination of all kinematic chains. To characterize human movement, we conducted a set of motion capture with position and orientation constraints of the hand in the horizontal plane. These acquisitions allowed to know the spatial and temporal evolution of the hand in the task space, for translation and rotation aspects. These acquired data were coupled with a playback method to analyze the intrinsic relations that link the task space to joint space of the model. The automatic generation scheme of realistic motion is based on a stack of task with a kinematic approach. The assumption used to simulate the action is to follow the shortest path in the task space while limiting the cost in the joint space. The scheme is characterized by a set of parameters. A global map of parameter adjustment enables the simulation of a class of realistic movements. Finally, this scheme is validated quantitatively and qualitatively with comparison between the simulation and the human gesture