Experimental Effort of Data Driven Human Motion Simulation in Automotive Assembly

Manns, Martin; Mengel, Stefan; Mauer, Markus Auf der

doi:10.1016/j.procir.2016.02.035

Cited by 14 publications

(4 citation statements)

References 11 publications

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“…Despite this advantage, DHS has some limitations: simulation is based on task division in subtasks and analysis for each static posture, providing an evaluation of the static task sequence and barely considering the dynamic aspects of human-system interaction [9]. Moreover, the simulation preparation phase is time-consuming, strongly depending on the analyst's experience, and can suffer from unnaturalness in posture prediction [10]. To overcome these limitations, motion capture systems could be used to analyze movements and behaviours of real users through dedicated systems, allowing a real time postural analysis on a continuous flow of actions, closer to real activities and it could be used also on-field [11].…”

Section: Research Backgroundmentioning

confidence: 99%

Digital Technologies to Redesign Automatic Machines with a Human-Centric Approach: Application in Industry

Grandi

Peruzzini

Khamaisi

et al. 2022

Advances in Transdisciplinary Engineering

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Human factors integration is definitely a transdisciplinary and urgent matter in modern factories. Despite the great surge in factory automation in recent years, human-machine interaction is still a crucial aspect and companies need to take care of the workers’ wellbeing and performance to enhance the overall system quality and productivity. Nevertheless, ergonomics is poorly considered during the design of complex industrial systems, such as automatic machinery, especially for the lack of practical methodologies and guidelines to promote human factors from the early stages of design or redesign. To overcome this issue, this work proposes a transdisciplinary approach to redesign automatic machinery in compliance with factory ergonomics, using a combination of digital technologies (e.g., digital human simulation, human physiological data monitoring). The paper defines a structure method and related tools to apply a human-centric approach to industrial cases and their validation of a real case, concerning the redesign of a packaging automatic machine. Results show how the proposed approach is useful to detect possible ergonomic issues at the shop floor, identifying in advance risky situations for the operators during operating or maintenance tasks, and leading to an optimized machine able to enhance the workers’ wellbeing and factory productivity at the same time.

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Section: Research Backgroundmentioning

confidence: 99%

Digital Technologies to Redesign Automatic Machines with a Human-Centric Approach: Application in Industry

Grandi

Peruzzini

Khamaisi

et al. 2022

Advances in Transdisciplinary Engineering

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“…A large amount of data can be collected during immersed commissioning which can later be used to drive behavior generation algorithms [22].…”

Section: Human-in-the-loop Commissioningmentioning

confidence: 99%

Integrated virtual commissioning of a ROS2-based collaborative and intelligent automation system

Erős

Dahl

Hanna

et al. 2019

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)

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In order to adapt to stricter system delivery and integration requirements, virtual commissioning (VC) has become a well adopted practice in industry. VC is getting increasingly integrated into the overall engineering process, where the control software is continuously tested with the virtual plant model. At the same time, collaborative and intelligent automation systems are becoming an important part of modern industries. In these complex systems, humans perform operations together with collaborative robots, intelligent machines and smart tools. However, performing VC of such complex, distributed and heterogeneous systems demands new ways of interfacing different hardware and software components. This paper discusses the requirements, process and results of integrated virtual commissioning of an industrial collaborative and intelligent automation system usecase. Moreover, this industrial use-case illustrates challenges and exemplifies the need to use the next generation Robot Operating System (ROS2) due to its robust communication layer as well as easy integration with smart devices and algorithms.

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“…Their work is extended by Du et al [DMHF16] transferring the approach to scenarios related to assembly workshops. Furthermore, Manns et al investigate the influence of input data to the effectiveness of this approach [MOM16] and point out the considerable requirements in both quality and quantity for adapting the methodology to common shop-floor motions [MMM16].…”

Section: Statistical Motion Synthesismentioning

confidence: 99%

A Probabilistic Steering Parameter Model for Deterministic Motion Planning Algorithms

Agethen

Gaisbauer

Rukzio³

2018

Computer Graphics Forum

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The simulation of two‐dimensional human locomotion in a bird's eye perspective is a key technology for various domains to realistically predict walk paths. The generated trajectories, however, are frequently deviating from reality due to the usage of simplifying assumptions. For instance, common deterministic motion planning algorithms predominantly utilize a set of static steering parameters (e.g. maximum acceleration or velocity of the agent) to simulate the walking behaviour of a person. This procedure neglects important influence factors, which have a significant impact on the spatio‐temporal characteristics of the finally resulting motion—such as the operator's physical conditions or the probabilistic nature of the human locomotor system. In overcome this drawback, this paper presents an approach to derive probabilistic motion models from a database of captured human motions. Although being initially designed for industrial purposes, this method can be applied to a wide range of use cases while considering an arbitrary number of dependencies (input) and steering parameters (output). To underline its applicability, a probabilistic steering parameter model is implemented, which models velocity, angular velocity and acceleration as a function of the travel distances, path curvature and height of a respective person. Finally, the technical performance and advantages of this model are demonstrated within an evaluation.

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Experimental Effort of Data Driven Human Motion Simulation in Automotive Assembly

Cited by 14 publications

References 11 publications

Digital Technologies to Redesign Automatic Machines with a Human-Centric Approach: Application in Industry

Digital Technologies to Redesign Automatic Machines with a Human-Centric Approach: Application in Industry

Integrated virtual commissioning of a ROS2-based collaborative and intelligent automation system

A Probabilistic Steering Parameter Model for Deterministic Motion Planning Algorithms

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