Högskolan i Skövde

This study examines how specific collaborative features for independent viewpoint control, collaborative pointing, sketching, and manikin representations support design reviews in a virtual environment. Participants conducted design reviews using the collaborative design tool Gravity Sketch while engaging with these features. Results show that friction situations were minimal, with viewpoint control eliminating the need for perspective adjustments. Collaborative pointing and sketching effectively clarified design modifications, while manikin representations aided discussions on ergonomics. The findings highlight how the evaluated features facilitate communication in remote design reviews.

Industry 5.0 advocates a human-centric approach where humans play a central role in the design and implementation of industrial technologies. Collaborative robots, with their adjustable safety functions, are key enabling technologies in this paradigm, especially for manual assembly tasks. This study investigates initial trust in collaborative robots by examining whether familiarization through virtual reality (VR) influences the applicability of various trust-related factors. Two groups of university engineering students participated: an Online group that evaluated the factors based solely on images and provided general information, and an In-Person group that engaged in a VR interaction with the robot before evaluation. Participants were asked to assess whether they found factors such as safety, usability, competence, predictability, and adaptability applicable to the robots, selecting "Yes", "No", or "I don’t know". In a follow-up question, they were then asked to rate each factor on a 5-point Likert scale. Results indicate that the In-Person group more frequently affirmed the applicability of the factors. Limitations include the use of only positively framed statements and the participants’ prior experience with industrial and collaborative robots. 

När forskare flyr Trumps USA får Europa inte missa chansen att ta emot dem. Nu finns en unik möjlighet för Sverige att bygga ut grundforskningen i en historiskt snabb expansion och rekrytera hundratals amerikanska forskare. Det skriver Oskar MacGregor och Maurice Lamb vid Högskolan i Skövde.

Aims: Recent world events have resulted in companies using remote meeting tools more often in design processes. The shift to remote meeting tools has had a notable impact on collaborative design activities, such as design reviews (DRs). When DRs depend on computer-aided design (CAD) software, the lack of direct support for CAD functionalities in videoconferencing applications introduces novel communication challenges, i.e. friction. This study investigates friction encountered in real world remote DRs when using a combination of standard CAD and videoconferencing applications. The objective was to understand the main sources of friction when carrying out DRs using a combination of CAD and videoconferencing applications.

Methods: At a single Swedish automobile manufacturer, 15 DRs of a fixture component were passively observed. These observations were subjected to a qualitative thematic analysis to identify categories and sources of friction during these DRs. The DRs were carried out using a combination of CATIA CAD software and Microsoft Teams for videoconferencing.

Results: The analysis of the 15 remote DRs identified four recurring friction categories: requesting specific viewpoints, indicating specific elements, expressing design change ideas, and evaluating ergonomics. Each category highlights specific challenges that were observed during the DRs and emerged due to constraints imposed by existing methods and technologies for remote meetings.

Conclusion: This study provides a framework for understanding the current sources of friction in remote DRs using videoconferencing tools. These insights can support the future development of DR software tools, guiding the integration of features that address these friction points. Additionally, the results serve as a guideline for organizations to implement methods that reduce friction in remote DRs and improve DR quality and efficacy.

Human motion prediction for tasks involving obstacle avoidance is critical for digital human modeling, robotics, and ergonomics. This study compares two approaches for predicting minimum clearance distance during upper extremity reaching tasks: an expanded 3D space version of the Steering Dynamics Model (SDM) and a perceived risk-based optimization motion prediction. The optimization-based method integrates biomechanical constraints and Bayesian Decision Theory to model perceived risk, while the SDM predicts emergent paths based on attractor-repeller dynamics. Both methods were tested using experimental data from fifteen participants, who performed reaching tasks around a 3D obstacle recorded with an IMU-based motion capture system. Results show that both methods improve minimum clearance distance predictions compared to a purely artificial sphere obstacle avoidance constraints approach. The SDM provides a computationally efficient alternative to the optimization-based approach while maintaining accuracy. However, the optimization-based method with perceived risk more closely aligns with experimental data, demonstrating the importance of cognitive modeling. The point cloud obstacle representation proved effective in both approaches. Future work should explore parameter tuning, subject-specific adaptations, and additional cognitive modeling techniques to enhance accuracy. These findings improve digital human simulations and real-time human-robot interaction models by integrating biomechanical and cognitive factors in motion prediction.

Occupant packaging design is usually done using computer-aided design (CAD) and digital human modelling (DHM) tools. These tools help engineers and designers explore and identify vehicle cabin configurations that meet accommodation targets. However, studies indicate that current working methods are complicated and iterative, leading to time-consuming design procedures and reduced investigations of the solution space, in turn meaning that successful design solutions may not be discovered. This paper investigates potential advantages and challenges in using an automated simulation-based multi-objective optimization (SBMOO) method combined with a DHM tool to improve the occupant packaging design process. Specifically, the paper studies how SBMOO using a genetic algorithm can address challenges introduced by human anthropometric and postural variability in occupant packaging design. The investigation focuses on a fabricated design scenario involving the spatial location of the seat and steering wheel, as well as seat angle, taking into account ergonomics objectives and constraints for various end-users. The study indicates that the SBMOO-based method can improve effectiveness and aid designers in considering human variability in the occupant packaging design process.

Remote design reviews are often carried out using video conferencing apps and are limited by the lack of immersive interaction, which is believed to be addressable by using extended reality (XR). It is argued that giving design review participants control over their viewpoint through XR might enhance the design review process. This study investigates whether enhancing camera control can improve collaborative problem-solving without XR. We propose that the ability to create one’s own cognitive map of a space through self-navigation is the basis for improvement, not XR technology specifically.

The experimental setup involves a collaborative puzzle-solving task with two distinct conditions: one with fixed camera perspectives and another allowing personal camera control. Teams of three engage in a task requiring the assembly of a 3D puzzle, where two of them have half of the solution and work to guide a third individual in a puzzle assembly task.

We aim to measure outcomes in terms of completion time, the number of errors, and user satisfaction. Preliminary results indicate a complex interaction between camera control and collaborative dynamics. I intend to discuss our methodology, share initial observations, and explore the implications of these findings.

The human musculoskeletal system’s inherent redundancies allow for infinite potential configurations for any given task. While sometimes seen as a problem for cognitive control systems, motor redundancy also fosters adaptability, learning, and resilience, making it essential for effective motor functioning (Latash, 2012). While many features of human motion and pose production have been identified, it remains unclear how cognitive systems quickly identify and enact motions given the scale of challenges introduced by motor redundancy. This study introduces an inverse kinematics solver, the Forward and Backward Reaching Inverse Kinematics solver (FABRIK) (Aristidou et al., 2016; Lamb et al., 2022). FABRIK uses a novel and lightweight approach to overcoming degree of freedom redundancy in multi-joint systems and may provide insights into human motor control. Initial validations of FABRIK for predicting human motion and pose data, demonstrate strong alignment with recorded data and are comparable to more computationally intensive state-of-the-art methods. We consider the implications of this relatively simple inverse kinematics solver for understanding how cognitive systems might deal with the challenges of motion planning in real time.