Charge cognitive

Résumé

La charge cognitive est une théorie développée par et Fred Paas qui explique les échecs ou les réussites des personnes essentiellement en activité d'apprentissage mais aussi en activité de résolution de problème. La théorie de la charge cognitive met en jeu la capacité de stockage d'informations en mémoire de travail et l'intégration de nouvelles informations. Elle est utile aux enseignants et pédagogues, et leur donne des conseils facilement applicables en situation d'apprentissage. Théorie Mémoire de travail La mémoire de travail ne peut gérer qu'un nombre limité d'informations à la fois, le nombre habituellement avancé étant de 5 à 9 informations, indiquées comme étant "Le nombre magique sept, plus ou moins deux" du Pr Miller de l'Université Harvard, dont les travaux furent publiés en 1956. Comme la mémoire de travail est limitée, il est nécessaire que les informations utiles à l'accomplissement d'une tâche puissent rentrer dans les limites de la mémoire de

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https://fr.wikipedia.org/wiki/Charge_cognitive

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Publications associées (70)

Publications associées

Chargement

Personnes associées (13)

Personnes associées

Chargement

Unités associées (12)

Unités associées

Chargement

Concepts associés (2)

Concepts associés

Chargement

Cours associés (4)

Cours associés

Chargement

Séances de cours associées (10)

Séances de cours associées

Chargement

Foot-Interfaces Control and Human-Robot Interaction in Four-Handed Manipulation

Jacob Hernandez Sanchez

Humans have a great capacity to perform complex manipulations. However, there are many tasks for which two hands are not enough, such as in surgery. For such tasks, a dyad of people is required. However, when not used to work together, a dyad collaboration can be intermittent, slow and prone to misunderstandings if relied solely on verbal cues. The current PhD thesis report concerns the design and control of foot interfaces to enable solo four-handed manipulations. In the first part, we present the platform design in five DoF, with position mapping and haptic force feedback. We tackle the known issue of fatigue when using position mapping, by partially compensating for the dynamics of the leg. Finally, we perform a series of feasibility validations on bipedal teleoperation in 3 and 4 and 5 DoF. In the second part, a behavioural study investigates a symmetric bipedal holding and transport of an object while working on it with the hands. This study sheds light to the human capacity to use the redundancy given by augmentation with the feet, to assist the task of the hands. We investigate the effect of shared-control for lower limb teleoperation. Two modalities are used: 1. synergistic control of two robotic arms with one foot, 2. force assistance. We evaluate these strategies in terms of objective and subjective metrics, such as physical and cognitive workload and fluency.Aiming at enabling individualized foot dexterous control, in the third part of the thesis, we addressed the problem of bio-mechanical coupling of foot rotations. This is done by detecting intention to grasp, and selectively easing this action while haptically constraining the foot gestures for tool alignment. A user study was conducted to evaluate our proposed approach in a surgical laparoscopic gripper.In the fourth and final part, we focus on investigating more demanding tasks for the feet, as well as the coordinated control of four hands, during hybrid-robotic laparoscopic surgery. One foot controls a camera, while the other one performs a grasping task. Noteworthy is that all four-arms can be controlled simultaneously. For easing the solo surgical task, we design haptic assistance, for autonomous grasping operated by the foot. Finally, we perform a systematic behavioural study to understand the effect of our haptic-shared-control, along with an assistance modality for camera tool-tracking. We cover uni-pedal, bipedal and four-handed task scenarios. Our main conclusion is that foot gestures can be conditioned with haptic feedback, to effectively control multiple degrees of freedom of a supernumerary robotic arm. Thereby enabling four-arm simultaneous manipulations. This is done specifically by leveraging 1. a foot kinesthetic haptic platform that allows for the use of two feet, 2. leg compensation, and virtual assistive impedance, which are useful to increase comfort and alleviate fatigue. 3. Hybridization of control mappings for foot gestures, with limited range of motion and oblique axes of rotation, 4. Haptic shared-control strategies for prehensile force assistance, coordination assistance, and DoF-individuation assistance. We found that robotic assistance is highly appreciated, and has an important role in simplifying four-handed tasks. Indeed, these are instrumental considerations to enable a more fluent, less demanding, and more performant interaction, in tasks where the feet are supplementing the task of hands.

EPFL2022

Chargement

Neuron splitting in compute-bound parallel network simulations enables runtime scaling with twice as many processors

Michael Lee Hines

Neuron tree topology equations can be split into two subtrees and solved on different processors with no change in accuracy, stability, or computational effort; communication costs involve only sending and receiving two double precision values by each subtree at each time step. Splitting cells is useful in attaining load balance in neural network simulations, especially when there is a wide range of cell sizes and the number of cells is about the same as the number of processors. For compute-bound simulations load balance results in almost ideal runtime scaling. Application of the cell splitting method to two published network models exhibits good runtime scaling on twice as many processors as could be effectively used with whole-cell balancing.

Springer Verlag2008

Chargement

Robotic systems are becoming more and more pervasive in modern industrial, scientific and personal activities through recent years and will play a fundamental role in the future society. Despite their increasing level of automation, teleoperation is still needed in many robotic applications. Human-Robot Interfaces (HRIs) are a central element in the diffusion of robots and are a crucial component to make them available to the use of most people. However, standard interfaces such as remote controllers still need time and extensive training to be proficiently mastered by users. Body-Machine Interfaces (BoMIs) represent a promising alternative to such devices as they leverage the innate ability of humans to finely control their movements. This thesis aims to provide new insights about humans' natural motor behaviors when interfacing with robots and to propose novel approaches for the implementation of HRIs based on body motion. The core contribution of this work is the design, realization and qualification of machine learning-based methods to translate the motion of a person into control inputs for a robot. The methods described here allowed naive users to effectively control real and simulated robots based on the processing of their body movements with a faster learning rate compared to classic interfaces. We extended our core algorithm to leverage knowledge about the natural organization of human motion resulting a more general method that was successfully applied for the control of a set of morphologically different machines. Through the implementation of an online adaptive functionality, we enabled users to modify their motor behaviour during teleoperation resulting in a lower perceived physical and cognitive workload and augmented performance. Human factors such as the sense of presence in virtual or distant environments, or the motor characteristics of distinct body areas are a key factor for advanced telerobotic applications. We studied the impact of the use of Virtual Reality for the control of non-anthropomorphic machines, and the effects of designing BoMIs based on different limbs opening to new knowledge about the effects of such factors in human-robot interaction. The design of a wearable haptic interface for drone operation showed the potential of augmenting their senses to perceive a distal environment through the sense of touch. Thanks to this novel design, nonexpert users were enabled to navigate drones through narrow passages with limited visibility, a task almost impossible to perform with standard interfaces.We believe that this thesis contributes to pave the way towards a deeper understanding of humans in human-robot interaction, as well as providing a new set of tools for the design of simple, intuitive interfaces with the goal of democratizing robotic teleoperation for the masses.

EPFL2021

Chargement

Foot-Interfaces Control and Human-Robot Interaction in Four-Handed Manipulation

Jacob Hernandez Sanchez

EPFL2022

EPFL2021