scholarly journals Haptic Devices Based on Real-Time Dynamic Models of Multibody Systems

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4794
Author(s):  
Nicolas Docquier ◽  
Sébastien Timmermans ◽  
Paul Fisette
Keyword(s):  
Real Time ◽  
Physical System ◽  
Dynamic Models ◽  
Haptic Feedback ◽  
Model Parameters ◽  
Sensors And Actuators ◽  
Multibody Modeling ◽  
Haptic Devices ◽  
Human In The Loop ◽  
Multibody Model

Multibody modeling of mechanical systems can be applied to various applications. Human-in-the-loop interfaces represent a growing research field, for which increasingly more devices include a dynamic multibody model to emulate the system physics in real-time. In this scope, reliable and highly dynamic sensors, to both validate those models and to measure in real-time the physical system behavior, have become crucial. In this paper, a multibody modeling approach in relative coordinates is proposed, based on symbolic equations of the physical system. The model is running in a ROS environment, which interacts with sensors and actuators. Two real-time applications with haptic feedback are presented: a piano key and a car simulator. In the present work, several sensors are used to characterize and validate the multibody model, but also to measure the system kinematics and dynamics within the human-in-the-loop process, and to ultimately validate the haptic device behavior. Experimental results for both developed devices confirm the interest of an embedded multibody model to enhance the haptic feedback performances. Besides, model parameters variations during the experiments illustrate the infinite possibilities that such model-based configurable haptic devices can offer.

scholarly journals Multibody-Based Piano Action: Validation of a Haptic Key

Machines ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 76
Author(s):  
Sébastien Timmermans ◽  
Bruno Dehez ◽  
Paul Fisette
Keyword(s):  
Real Time ◽  
Force Feedback ◽  
Haptic Feedback ◽  
Fem Analysis ◽  
Haptic Device ◽  
Multibody Model ◽  
Custom Made ◽  
Transmitted Force ◽  
Grand Piano ◽  
The Voice

A piano key prototype actuated by a custom-made linear actuator is proposed to enhance the touch of digital pianos by reproducing the force feedback of an acoustic piano action. This paper presents the design and the validation of the haptic device. The approach exploits a multibody model to compute the action dynamics and the corresponding force on the key in real time. More specifically, a grand piano model that includes the five action bodies, its geometry and the specific force laws, is computed in the haptic device. A presizing step along with Finite Element Method (FEM) analysis produced an especially made actuator satisfying the design requirements, in particular the highly dynamic nature of the force to be transmitted. Force peaks, up to 50 (N) in less than 20 (ms), are reachable with low power consumption. Compared to previous solutions: (i) the key physical characteristics are preserved; (ii) the feedback is based on a real-time multibody model that is easily configurable and interchangeable; (iii) an experimental validation of the actuator within the prototype is developed and demonstrates its feasibility. The results confirm that the voice coil can produce suitable haptic feedback. In particular, rendering a grand piano action within the device shows promising haptic force profiles.

A novel approach to the real-time modelling of large urban drainage systems

1997 ◽  
Vol 36 (8-9) ◽  
pp. 19-24 ◽  
Author(s):  
Richard Norreys ◽  
Ian Cluckie
Keyword(s):  
Real Time ◽  
Dynamic Models ◽  
Drainage System ◽  
Radar Data ◽  
Urban Drainage ◽  
Real Time Control ◽  
Empirical Modelling ◽  
Time Control ◽  
Novel Approach ◽  
Non Linear Systems

Conventional UDS models are mechanistic which though appropriate for design purposes are less well suited to real-time control because they are slow running, difficult to calibrate, difficult to re-calibrate in real time and have trouble handling noisy data. At Salford University a novel hybrid of dynamic and empirical modelling has been developed, to combine the speed of the empirical model with the ability to simulate complex and non-linear systems of the mechanistic/dynamic models. This paper details the ‘knowledge acquisition module’ software and how it has been applied to construct a model of a large urban drainage system. The paper goes on to detail how the model has been linked with real-time radar data inputs from the MARS c-band radar.

scholarly journals Real-time automatic uncertainty estimation of coseismic single rectangular fault model using GNSS data

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Keitaro Ohno ◽  
Yusaku Ohta ◽  
Satoshi Kawamoto ◽  
Satoshi Abe ◽  
Ryota Hino ◽  
...  
Keyword(s):  
Real Time ◽  
Disaster Response ◽  
Order Approximation ◽  
Nonlinear Problems ◽  
Large Earthquake ◽  
Fault Model ◽  
Deformation Monitoring ◽  
Model Parameters ◽  
The Sea Of Japan ◽  
Plate Interface

AbstractRapid estimation of the coseismic fault model for medium-to-large-sized earthquakes is key for disaster response. To estimate the coseismic fault model for large earthquakes, the Geospatial Information Authority of Japan and Tohoku University have jointly developed a real-time GEONET analysis system for rapid deformation monitoring (REGARD). REGARD can estimate the single rectangular fault model and slip distribution along the assumed plate interface. The single rectangular fault model is useful as a first-order approximation of a medium-to-large earthquake. However, in its estimation, it is difficult to obtain accurate results for model parameters due to the strong effect of initial values. To solve this problem, this study proposes a new method to estimate the coseismic fault model and model uncertainties in real time based on the Bayesian inversion approach using the Markov Chain Monte Carlo (MCMC) method. The MCMC approach is computationally expensive and hyperparameters should be defined in advance via trial and error. The sampling efficiency was improved using a parallel tempering method, and an automatic definition method for hyperparameters was developed for real-time use. The calculation time was within 30 s for 1 × 106 samples using a typical single LINUX server, which can implement real-time analysis, similar to REGARD. The reliability of the developed method was evaluated using data from recent earthquakes (2016 Kumamoto and 2019 Yamagata-Oki earthquakes). Simulations of the earthquakes in the Sea of Japan were also conducted exhaustively. The results showed an advantage over the maximum likelihood approach with a priori information, which has initial value dependence in nonlinear problems. In terms of application to data with a small signal-to-noise ratio, the results suggest the possibility of using several conjugate fault models. There is a tradeoff between the fault area and slip amount, especially for offshore earthquakes, which means that quantification of the uncertainty enables us to evaluate the reliability of the fault model estimation results in real time.

Towards real-time fire data synthesis using numerical simulations

2021 ◽  
pp. 073490412199344
Author(s):  
Wolfram Jahn ◽  
Frane Sazunic ◽  
Carlos Sing-Long
Keyword(s):  
Real Time ◽  
Computational Fluid Dynamic ◽  
Dynamic Models ◽  
Fluid Dynamic ◽  
Near Field ◽  
Computing Time ◽  
Temperature Correction ◽  
Dynamic Simulations ◽  
Conservation Of Energy ◽  
Fire Scenarios

Synthesising data from fire scenarios using fire simulations requires iterative running of these simulations. For real-time synthesising, faster-than-real-time simulations are thus necessary. In this article, different model types are assessed according to their complexity to determine the trade-off between the accuracy of the output and the required computing time. A threshold grid size for real-time computational fluid dynamic simulations is identified, and the implications of simplifying existing field fire models by turning off sub-models are assessed. In addition, a temperature correction for two zone models based on the conservation of energy of the hot layer is introduced, to account for spatial variations of temperature in the near field of the fire. The main conclusions are that real-time fire simulations with spatial resolution are possible and that it is not necessary to solve all fine-scale physics to reproduce temperature measurements accurately. There remains, however, a gap in performance between computational fluid dynamic models and zone models that must be explored to achieve faster-than-real-time fire simulations.

scholarly journals ATCO radar training assessment and flight efficiency: the correlation between trainees’ scores and fuel consumption in real-time simulations

2020 ◽  
pp. 1-17
Author(s):  
T. Rogošić ◽  
B. Juričić ◽  
F. Aybek Çetek ◽  
Z. Kaplan
Keyword(s):  
Real Time ◽  
Fuel Consumption ◽  
Basic Training ◽  
Air Traffic Controller ◽  
Training Assessment ◽  
Assessment Scores ◽  
Human In The Loop ◽  
Assessment Standards ◽  
Two Parameters ◽  
Real Time Simulations

ABSTRACT Air traffic controller training is highly regulated but lacks prescribed common assessment criteria and methods to evaluate trainees at the level of basic training and consideration of how trainees in fluence flight efficiency. We investigated whether there is a correlation between two parameters, viz. the trainees’ assessment score and fuel consumption, obtained and calculated after real-time human-in-the-loop radar simulations within the ATCOSIMA project. Although basic training assessment standards emphasise safety indicators, it was expected that trainees with higher assessment scores would achieve better flight efficiency, i.e. less fuel consumption. However, the results showed that trainees’ assessment scores and fuel consumption did not correlate in the expected way, leading to several conclusions.

scholarly journals Big data actionable intelligence architecture

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Tian J. Ma ◽  
Rudy J. Garcia ◽  
Forest Danford ◽  
Laura Patrizi ◽  
Jennifer Galasso ◽  
...  
Keyword(s):  
Big Data ◽  
Real Time ◽  
Digital Media ◽  
Decision Makers ◽  
Time Data ◽  
Human In The Loop ◽  
Course Of Action ◽  
Insufficient Time ◽  
Data Source ◽  
Different Sources

AbstractThe amount of data produced by sensors, social and digital media, and Internet of Things (IoTs) are rapidly increasing each day. Decision makers often need to sift through a sea of Big Data to utilize information from a variety of sources in order to determine a course of action. This can be a very difficult and time-consuming task. For each data source encountered, the information can be redundant, conflicting, and/or incomplete. For near-real-time application, there is insufficient time for a human to interpret all the information from different sources. In this project, we have developed a near-real-time, data-agnostic, software architecture that is capable of using several disparate sources to autonomously generate Actionable Intelligence with a human in the loop. We demonstrated our solution through a traffic prediction exemplar problem.

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