Santos

Abdel‐Malek, Karim; Arora, Jasbir S.; Bhatt, Ramesh S.; Farrell, Kimberly; Murphy, Chris; Kregel, Kevin C.

doi:10.1016/b978-0-12-816713-7.00006-4

Cited by 8 publications

(3 citation statements)

References 48 publications

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“…high stature, high BMI). In [6], terms are added in the IK problem to generate motions that account for external loads and interal efforts minimization, but only the equations of statics are considered. Overall, these kinematic-based methods lead to unrealistic whole-body motions and inaccurate estimations of the internal body efforts.…”

Section: B Dhm Software and Whole-body Animationmentioning

confidence: 99%

Workstation Suitability Maps: Generating Ergonomic Behaviors on a Population of Virtual Humans With Multi-Task Optimization

Zhong,

Weistroffer,

Mouret

et al. 2023

IEEE Robot. Autom. Lett.

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In industrial workstations, the morphology of the worker is a key factor for the feasibility and the ergonomics of an activity. Existing digital human modeling tools can simulate different morphologies at work, but hardly scale to a large population of workers because of limited consideration of morphologyspecific behaviors and computational cost. This paper presents a framework to efficiently evaluate the suitability of a workstation over a large population of workers in a physics-based simulation. Activities are simulated through a two-step optimization process, involving a quadratic-programming-based whole-body controller and a multi-task optimizer for behavioral adaptation. On a screwdriving scenario, we demonstrate how our framework can help ergonomists improve workstation designs thanks to the resulting suitability maps where generated behaviors are optimized for each morphology w.r.t. ergonomics and performance.

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Section: B Dhm Software and Whole-body Animationmentioning

confidence: 99%

Workstation Suitability Maps: Generating Ergonomic Behaviors on a Population of Virtual Humans With Multi-Task Optimization

Zhong,

Weistroffer,

Mouret

et al. 2023

IEEE Robot. Autom. Lett.

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“…However, understanding the dynamics of these systems is imperative for effectively designing and optimizing them to cater diverse applications [3]. Efficient modeling and simulation [4,5] techniques have a high demand in many fields including engineering, physics and biology to understand and predict the behavior of complex systems depending upon time [6,7]. Numerical techniques such as Euler's [8],…”

Section: Introductionmentioning

confidence: 99%

An Oscillatory Deep Neural Network for Coupled Electrical Circuits

Rahman,

Makhdoom,

Rashid

et al. 2024

Preprint

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Electronic systems share an indispensable role in almost every modern industry and are therefore continuously evolving into more advanced and complex versions. Consequently, such systems need to be tackled with some cutting-edge techniques. Among a number of analytical and numerical techniques of this era, Artificial Neural Networks (ANNs) have grabbed attention due to their universality and robustness on assigned tasks. In this work, an oscillatory Deep Neural Network (DNN) model has been proposed with an oscillatory activation function and specific layers’ structure to learn the dynamics of coupled LC-series circuits. The DNN model being suggested is flexible, easy to implement, and capable of diligently recovering the vibrating patterns of underlying dynamical systems. Outputs from the network are being compared with the results of LSODA numerical solvers. An error analysis for different time spans has also being performed, validating the successful recovery of solutions to the modeled problem, which is evident to the competency of proposed technique.

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“…These biomechanical quantities can be used as a measure for ergonomic evaluation . Examples of prevalent biomechanical simulation frameworks are OpenSim (Seth et al 2018), the AnyBody Modelling System (Damsgaard et al 2006;Rasmussen 2019) and SANTOS (Abdel-Malek et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Challenges in interaction modelling with digital human models – A systematic literature review of interaction modelling approaches

Wolf¹,

Miehling²,

Wartzack³

2020

Ergonomics

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Digital human models (DHM) allow for a proactive ergonomic assessment of products by applying different models describing the user-product interaction. In engineering design, DHM tools are currently not established as computer-aided ergonomics tools, since (among other reasons) the interaction models are either cumbersome to use, unstandardised, time-demanding or not trustworthy. To understand the challenges in interaction modelling, we conducted a systematic literature review with the aim of identification, classification and examination of existing interaction models. A schematic user-product interaction model for DHM is proposed, abstracting existing models and unifying the corresponding terminology. Additionally, nine general approaches to proactive interaction modelling were identified by classifying the reviewed interaction models. The approaches are discussed regarding their scope, limitations, strength and weaknesses. Ultimately, the literature review revealed that prevalent interaction models cannot be considered unconditionally suitable for engineering design since none of them offer a satisfactory combination of genuine proactivity and universal validity.Practitioner summary: This contribution presents a systematic literature review conducted to identify, classify and examine existing proactive interaction modelling approaches for digital human models in engineering design. Ultimately, the literature review revealed that prevalent interaction models cannot be considered unconditionally suitable for engineering design since none of them offer a satisfactory combination of genuine proactivity and universal validity.

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Santos

Cited by 8 publications

References 48 publications

Workstation Suitability Maps: Generating Ergonomic Behaviors on a Population of Virtual Humans With Multi-Task Optimization

Workstation Suitability Maps: Generating Ergonomic Behaviors on a Population of Virtual Humans With Multi-Task Optimization

An Oscillatory Deep Neural Network for Coupled Electrical Circuits

Challenges in interaction modelling with digital human models – A systematic literature review of interaction modelling approaches

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