A Framework to Illustrate Kinematic Behavior of Mechanisms by Haptic Feedback

The kinematic properties of mechanisms are well known by the researchers and teachers. The theory based on the study of Jacobian matrices allows us to explain, for example, the singular configuration. However, in many cases, the physical sense of such properties is difficult to explain to students. The aim of this article is to use haptic feedback to render to the user the signification of different kinematic indices. The framework uses a Phantom Omni and a serial and parallel mechanism with two degrees of freedom. The end-effector of both mechanisms can be moved either by classical mouse, or Phantom Omni with or without feedback

Contact identification for assembly-disassembly simulation with a haptic device

Assembly/Disassembly (A/D) simulations using haptic devices are facing difficulties while simulating insertion/extraction operations such as removing cylinders from holes. In order to address this configuration as well as others, an approach based on contact identification between components is presented in this paper. This approach can efficiently contribute either to a new A/D simulation preparation process relying on two types of shape representations (mesh and CAD NURBS models), or directly to the real time simulation process when it is performed with 6D haptic devices. The model processing pipeline is described and illustrated to show how information can be propagated and used for contact detection. Then, the contact identification process is introduced and illustrated through an exampl

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans

The combination of physical sensors and computational models to provide additional information about system states, inputs and/or parameters, in what is known as virtual sensing, is becoming increasingly popular in many sectors, such as the automotive, aeronautics, aerospatial, railway, machinery, robotics and human biomechanics sectors. While, in many cases, control-oriented models, which are generally simple, are the best choice, multibody models, which can be much more detailed, may be better suited to some applications, such as during the design stage of a new product

Control of Elastic Soft Robots based on Real-Time Finite Element Method

International audienceIn this paper, we present a new method for the control of soft robots with elastic behavior, piloted by several actuators. The central contribution of this work is the use of the Finite Element Method (FEM), computed in real-time, in the control algorithm. The FEM based simulation computes the nonlinear deformations of the robots at interactive rates. The model is completed by Lagrange multipliers at the actuation zones and at the end-effector position. A reduced compliance matrix is built in order to deal with the necessary inversion of the model. Then, an iterative algorithm uses this compliance matrix to find the contribution of the actuators (force and/or position) that will deform the structure so that the terminal end of the robot follows a given position. Additional constraints, like rigid or deformable obstacles, or the internal characteristics of the actuators are integrated in the control algorithm. We illustrate our method using simulated examples of both serial and parallel structures and we validate it on a real 3D soft robot made of silicon

Visual motion processing and human tracking behavior

The accurate visual tracking of a moving object is a human fundamental skill that allows to reduce the relative slip and instability of the object's image on the retina, thus granting a stable, high-quality vision. In order to optimize tracking performance across time, a quick estimate of the object's global motion properties needs to be fed to the oculomotor system and dynamically updated. Concurrently, performance can be greatly improved in terms of latency and accuracy by taking into account predictive cues, especially under variable conditions of visibility and in presence of ambiguous retinal information. Here, we review several recent studies focusing on the integration of retinal and extra-retinal information for the control of human smooth pursuit.By dynamically probing the tracking performance with well established paradigms in the visual perception and oculomotor literature we provide the basis to test theoretical hypotheses within the framework of dynamic probabilistic inference. We will in particular present the applications of these results in light of state-of-the-art computer vision algorithms

A MECHANISTIC APPROACH TO POSTURAL DEVELOPMENT IN CHILDREN

Upright standing is intrinsically unstable and requires active control. The central nervous system's feedback process is the active control that integrates multi-sensory information to generate appropriate motor commands to control the plant (the body with its musculotendon actuators). Maintaining standing balance is not trivial for a developing child because the feedback and the plant are both developing and the sensory inputs used for feedback are continually changing. Knowledge gaps exist in characterizing the critical ability of adaptive multi-sensory reweighting for standing balance control in children. Furthermore, the separate contributions of the plant and feedback and their relationship are poorly understood in children, especially when considering that the body is multi-jointed and feedback is multi-sensory. The purposes of this dissertation are to use a mechanistic approach to study multi-sensory abilities of typically developing (TD) children and children with Developmental Coordination Disorder (DCD). The specific aims are: 1) to characterize postural control under different multi-sensory conditions in TD children and children with DCD; 2) to characterize the development of adaptive multi-sensory reweighting in TD children and children with DCD; and, 3) to identify the plant and feedback for postural control in TD children and how they change in response to visual reweighting. In the first experiment (Aim 1), TD children, adults, and 7-year-old children with DCD are tested under four sensory conditions (no touch/no vision, with touch/no vision, no touch/with vision, and with touch/with vision). We found that touch robustly attenuated standing sway in all age groups. Children with DCD used touch less effectively than their TD peers and they also benefited from using vision to reduce sway. In the second experiment (Aim 2), TD children (4- to 10-year-old) and children with DCD (6- to 11-year-old) were presented with simultaneous small-amplitude touch bar and visual scene movement at 0.28 and 0.2 Hz, respectively, within five conditions that independently varied the amplitude of the stimuli. We found that TD children can reweight to both touch and vision from 4 years on and the amount of reweighting increased with age. However, multi-sensory fusion (i.e., inter-modal reweighting) was only observed in the older children. Children with DCD reweight to both touch and vision at a later age (10.8 years) than their TD peers. Even older children with DCD do not show advanced multisensory fusion. Two signature deficits of multisensory reweighting are a weak vision reweighting and a general phase lag to both sensory modalities. The final aim involves closed-loop system identification of the plant and feedback using electromyography (EMG) and kinematic responses to a high- or low-amplitude visual perturbation and two mechanical perturbations in children ages six and ten years and adults. We found that the plant is different between children and adults. Children demonstrate a smaller phase difference between trunk and leg than adults at higher frequencies. Feedback in children is qualitatively similar to adults. Quantitatively, children show less phase advance at the peak of the feedback curve which may be due to a longer time delay. Under the high and low visual amplitude conditions, children show less gain change (interpreted as reweighting) than adults in the kinematic and EMG responses. The observed kinematic and EMG reweighting are mainly due to the different use of visual information by the central nervous system as measured by the open-loop mapping from visual scene angle to EMG activity. The plant and the feedback do not contribute to reweighting