| 1. |
- Billing, Erik, PhD, 1981-, et al.
(författare)
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Automatic Selection of Viewpoint for Digital Human Modelling
- 2020
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Ingår i: DHM2020. - Amsterdam : IOS Press. - 9781643681047 - 9781643681054 ; , s. 61-70
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Konferensbidrag (refereegranskat)abstract
- During concept design of new vehicles, work places, and other complex artifacts, it is critical to assess positioning of instruments and regulators from the perspective of the end user. One common way to do these kinds of assessments during early product development is by the use of Digital Human Modelling (DHM). DHM tools are able to produce detailed simulations, including vision. Many of these tools comprise evaluations of direct vision and some tools are also able to assess other perceptual features. However, to our knowledge, all DHM tools available today require manual selection of manikin viewpoint. This can be both cumbersome and difficult, and requires that the DHM user possesses detailed knowledge about visual behavior of the workers in the task being modelled. In the present study, we take the first steps towards an automatic selection of viewpoint through a computational model of eye-hand coordination. We here report descriptive statistics on visual behavior in a pick-and-place task executed in virtual reality. During reaching actions, results reveal a very high degree of eye-gaze towards the target object. Participants look at the target object at least once during basically every trial, even during a repetitive action. The object remains focused during large proportions of the reaching action, even when participants are forced to move in order to reach the object. These results are in line with previous research on eye-hand coordination and suggest that DHM tools should, by default, set the viewpoint to match the manikin’s grasping location.
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| 2. |
- Brolin, Erik, 1984-, et al.
(författare)
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Skewed Boundary Confidence Ellipses for Anthropometric Data
- 2020
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Ingår i: DHM2020. - Amsterdam : IOS Press. - 9781643681047 - 9781643681054 ; , s. 18-27
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Konferensbidrag (refereegranskat)abstract
- Some anthropometric measurements, such as body weight often show a positively skewed distribution. Different types of transformations can be applied when handling skewed data in order to make the data more normally distributed. This paper presents and visualises how square root, log normal and, multiplicative inverse transformations can affect the data when creating boundary confidence ellipses. The paper also shows the difference of created manikin families, i.e. groups of manikin cases, when using transformed distributions or not, for three populations with different skewness. The results from the study show that transforming skewed distributions when generating confidence ellipses and boundary cases is appropriate to more accurately consider this type of diversity and correctly describe the shape of the actual skewed distribution. Transforming the data to create accurate boundary confidence regions is thought to be advantageous, as this would create digital manikins with enhanced accuracy that would produce more realistic and accurate simulations and evaluations when using DHM tools for the design of products and workplaces.
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| 3. |
- Darwish, Amena, et al.
(författare)
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Learning Individual Driver’s Mental Models Using POMDPs and BToM
- 2020
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Ingår i: DHM2020. - Amsterdam : IOS Press. - 9781643681047 - 9781643681054 ; , s. 51-60
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Konferensbidrag (refereegranskat)abstract
- Advanced driver assistant systems are supposed to assist the driver and ensure their safety while at the same time providing a fulfilling driving experience that suits their individual driving styles. What a driver will do in any given traffic situation depends on the driver’s mental model which describes how the driver perceives the observable aspects of the environment, interprets these aspects, and on the driver’s goals and beliefs of applicable actions for the current situation. Understanding the driver’s mental model has hence received great attention from researchers, where defining the driver’s beliefs and goals is one of the greatest challenges. In this paper we present an approach to establish individual drivers’ temporal-spatial mental models by considering driving to be a continuous Partially Observable Markov Decision Process (POMDP) wherein the driver’s mental model can be represented as a graph structure following the Bayesian Theory of Mind (BToM). The individual’s mental model can then be automatically obtained through deep reinforcement learning. Using the driving simulator CARLA and deep Q-learning, we demonstrate our approach through the scenario of keeping the optimal time gap between the own vehicle and the vehicle in front.
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| 4. |
- Igelmo, Victor, 1992-, et al.
(författare)
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Aiding Observational Ergonomic Evaluation Methods Using MOCAP Systems Supported by AI-Based Posture Recognition
- 2020
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Ingår i: DHM2020. - Amsterdam : IOS Press. - 9781643681054 - 9781643681047 ; , s. 419-429
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Konferensbidrag (refereegranskat)abstract
- Observational ergonomic evaluation methods have inherent subjectivity. Observers’ assessment results might differ even with the same dataset. While motion capture (MOCAP) systems have improved the speed and the accuracy of motiondata gathering, the algorithms used to compute assessments seem to rely on predefined conditions to perform them. Moreover, the authoring of these conditions is not always clear. Making use of artificial intelligence (AI), along with MOCAP systems, computerized ergonomic assessments can become more alike to human observation and improve over time, given proper training datasets. AI can assist ergonomic experts with posture detection, useful when using methods that require posture definition, such as Ovako Working Posture Assessment System (OWAS). This study aims to prove the usefulness of an AI model when performing ergonomic assessments and to prove the benefits of having a specialized database for current and future AI training. Several algorithms are trained, using Xsens MVN MOCAP datasets, and their performance within a use case is compared. AI algorithms can provide accurate posture predictions. The developed approach aspires to provide with guidelines to perform AI-assisted ergonomic assessment based on observation of multiple workers.
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| 5. |
- Iriondo Pascual, Aitor, 1993-, et al.
(författare)
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Implementation of Ergonomics Evaluation Methods in a Multi-Objective Optimization Framework
- 2020
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Ingår i: DHM2020. - Amsterdam : IOS Press. - 9781643681054 - 9781643681047 ; , s. 361-371
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Konferensbidrag (refereegranskat)abstract
- Simulations of future production systems enable engineers to find effective and efficient design solutions with fewer physical prototypes and fewer reconstructions. This can save development time and money and be more sustainable. Better design solutions can be found by linking simulations to multiobjective optimization methods to optimize multiple design objectives. When production systems involve manual work, humans and human activity should be included in the simulation. This can be done using digital human modeling (DHM) software which simulates humans and human activities and can be used to evaluate ergonomic conditions. This paper addresses challenges related to including existing ergonomics evaluation methods in the optimization framework. This challenge arises because ergonomics evaluation methods are typically developed to enable people to investigate ergonomic conditions by observing real work situations. The methods are rarely developed to be used by computer algorithms to draw conclusions about ergonomic conditions. This paper investigates how to adapt ergonomics evaluation methods to implement the results as objectives in the optimization framework. This paper presents a use case of optimizing a workstation using two different approaches: 1) an observational ergonomics evaluation method, and 2) a direct measurement method. Both approaches optimized two objectives: the average ergonomics results, and the 90th percentile ergonomics results.
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| 6. |
- Kolbeinsson, Ari, et al.
(författare)
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Employing UX Processes for More Focused Development in Research Projects
- 2020
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Ingår i: DHM2020. - Amsterdam : IOS Press. - 9781643681047 - 9781643681054 ; , s. 288-298
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Konferensbidrag (refereegranskat)abstract
- The aim of this paper is to highlight some benefits of incorporating usability/user experience (UX) approaches in the software development process of research projects advancing digital human modeling (DHM), and how these processes, approaches, and methods can help keeping the development process more focused and efficient. Research projects that contain large software development components may receive funding only to complete the core tasks, and including additional persons in a project may seem like a waste of resources. This paper introduces user research that relied on a UX approach called contextual inquiry to ascertain user goals and how those might be translated into features for DHM named IMMA that has been developed as a part of numerous research projects in the last decade. The goal of the study is to support DHM development in general through highlighting methods and approaches that can be used, with specific results aimed to support the continued development of IMMA. Results clearly show that existing functions do not support the goals of the user group examined, and highlights the need of understanding user goals and creating functions to support achieving those goals, rather than assuming what functionalities might be needed. By understanding user goals, interpreting those into activities and functionalities time and resources can be used more effectively, which is important for small to medium research projects, where both time and budget may be limited.
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| 7. |
- Kondyli, Vasiliki, 1989-, et al.
(författare)
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Multimodality on the Road : Towards Evidence-Based Cognitive Modelling of Everyday Roadside Human Interactions
- 2020
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Ingår i: Advances in Transdisciplinary Engineering. - : IOS Press. - 9781643681047 - 9781643681054 ; , s. 131-142
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Konferensbidrag (refereegranskat)abstract
- We propose an evidence based methodology for the systematic analysis and cognitive characterisation of multimodal interactions in naturalistic roadside situations such as driving, crossing a street etc. Founded on basic human modalities of embodied interaction, the proposed methodology utilises three key characteristics crucial to roadside situations, namely: explicit and implicit mode of interaction, formal and informal means of signalling, and levels of context-specific (visual) attention. Driven by the fine-grained interpretation and modelling of human behaviour in naturalistic settings, we present an application of the proposed model with examples from a work-in-progress dataset consisting of baseline multimodal interaction scenarios and variations built therefrom with a particular emphasis on joint attention and diversity of modalities employed. Our research aims to open up an interdisciplinary frontier for the human-centred design and evaluation of artificial cognitive technologies (e.g., autonomous vehicles, robotics) where embodied (multimodal) human interaction and normative compliance are of central significance.
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| 8. |
- Lindblom, Jessica, 1969-, et al.
(författare)
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Narrowing the Gap of Cognitive and Physical Ergonomics in DHM through Embodied Tool Use
- 2020
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Ingår i: DHM2020. - Amsterdam : IOS Press. - 9781643681047 - 9781643681054 ; , s. 311-322
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Konferensbidrag (refereegranskat)abstract
- The fields of human factors and ergonomics are systemic by nature, focusing on studying complex interaction between human and technology. However, the levels of explanation have resulted in physical or cognitive ergonomics. Modern understandings of human cognition and technology-mediated interaction, such as embodied cognition, activity theory and user experience (UX) is used as a frame of reference to analyze and illustrate the usage of a digital human modeling (DHM) tool in practice. In so doing, we try to narrow the gap between physical and cognitive ergonomics through embodied tool use. An identified core problem is to understand how a 2D devices should properly interact within 3D objects and manikins in a DMH tool that results in negative UX. The embodied concept of body schema clarifies the cognitive foundation for the negative UX. Some future work is presented, which could be beneficial for DHM, and, in the long run, promote a positive UX at work for various end-users of DHM tools.
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| 9. |
- Ljung, Oskar, et al.
(författare)
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Integration of Simulation and Manufacturing Engineering Software - Allowing Work Place Optimization Based on Time and Ergonomic Parameters
- 2020
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Ingår i: DHM2020. - Amsterdam : IOS Press. - 9781643681047 - 9781643681054 ; , s. 342-347
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Konferensbidrag (refereegranskat)abstract
- There is a constant strive in industry to be competitive on the market, to manufacture with quality and productivity. At the same time, it is important to offer workers a sustainable work life. Research has shown a clear relationship between poor ergonomics and productivity losses and quality deficiencies, e.g. due to assembly errors, which also causes large costs for companies. In spite of the abovementioned relationship, productivity, ergonomics and quality are commonly treated separately in factory, line and workstation planning. To improve the factory, line and workstation planning, make it more efficient, ergonomic and to improve quality this paper proposes a concept that enables line balancing that considers two parameters in parallel, assembly time and ergonomic load as well as add possibility for mathematical optimization. The concept has been developed in a participative and iterative process. Two software tools and a simulation platform, the digital human modelling tool IPS IMMA, the balancing tool AVIX and the optimization platform EPP, have been used to demonstrate the concept. An integrated solution is formed. The integrated demonstration tool shows promising results. The demonstrator provides the possibility to manually optimize ergonomics and time in parallel, a relatively unique functionality.
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| 10. |
- Reinhard, René, et al.
(författare)
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The Use and Usage of Virtual Reality Technologies in Planning and Implementing New Workstations
- 2020
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Ingår i: DHM2020. - Amsterdam : IOS Press. - 9781643681047 - 9781643681054 ; , s. 388-397
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Konferensbidrag (refereegranskat)abstract
- Virtual reality (VR) technologies can support the planning and implementation of new workstations in various industry sectors, including in automotive assembly. Starting in the early planning stages, VR can help in identifying potential problems of new design ideas, e.g. through ergonomics analyses. Designers can then quickly change the virtual representations of new workstations to test solutions for the emerging difficulties. For this purpose, the actions and motions of prospective workers can be captured while they perform the work tasks in VR. The information can also be used as input for digital human modelling (DHM) tools, to instruct biomechanical human models. The DHM tools can then construct families of manikins that differ on anthropometric characteristics, like height, to simulate work processes. This paper addresses both existing technologies for gathering data on human actions and motions during VR usage and ways in which these data can be used to assist in designing new workstations. Here, a novel approach to translate a VR user’s actions into instructions for DHM tools through an event-based instruction sampling method is presented. Further, the challenges for utilizing VR are discussed through an industrial use case of the manual assembly of flexible cables in an automotive context.
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