Browsing by Author "Eimontaite, Iveta"

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    Data: Dynamic Graphical Instructions Result in Improved Attitudes and Decreased Task Completion Time in Human–Robot Co-Working: An Experimental Manufacturing Study
    (Cranfield University, 2023-08-08 17:52) Eimontaite, Iveta; Cameron, David
    This study explores how dynamic graphical signage could aid a manufacturing task. Forty employees from one UK manufacturing company participated in a field experiment to complete a precision pick-and-place task working in conjunction with a collaborative robotic arm. Twenty-one participants completed the task with the support of dynamic graphical signage that provided information about the robot and the activity, while the rest completed the same task with no signage. Participants accuracy, response time, negative attitudes to robot, and outcome expectancy were assessed in this study. Data from: Eimontaite, I.; Cameron, D.; Rolph, J.; Mokaram, S.; Aitken, J.M.; Gwilt, I. Dynamic GraphicalInstructions Result in ImprovedAttitudes and Decreased TaskCompletion Time in Human–Robot Co-Working: An ExperimentalManufacturing Study. Sustainability 2022, 14
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    Dual arm co-manipulation architecture with enhanced human–robot communication for large part manipulation
    (MDPI, 2020-10-29) Ibarguren, Aitor; Eimontaite, Iveta; Outón, José Luis; Fletcher, Sarah
    The emergence of collaborative robotics has had a great impact on the development of robotic solutions for cooperative tasks nowadays carried out by humans, especially in industrial environments where robots can act as assistants to operators. Even so, the coordinated manipulation of large parts between robots and humans gives rise to many technical challenges, ranging from the coordination of both robotic arms to the human–robot information exchange. This paper presents a novel architecture for the execution of trajectory driven collaborative tasks, combining impedance control and trajectory coordination in the control loop, as well as adding mechanisms to provide effective robot-to-human feedback for a successful and satisfactory task completion. The obtained results demonstrate the validity of the proposed architecture as well as its suitability for the implementation of collaborative robotic systems.
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    Dynamic graphical instructions result in improved attitudes and decreased task completion time in human–robot co-working: an experimental manufacturing study
    (MDPI, 2022-03-11) Eimontaite, Iveta; Cameron, David; Rolph, Joe; Mokaram, Saeid; Aitken, Jonathan M.; Gwilt, Ian; Law, James
    Collaborative robots offer opportunities to increase the sustainability of work and workforces by increasing productivity, quality, and efficiency, whilst removing workers from hazardous, repetitive, and strenuous tasks. They also offer opportunities for increasing accessibility to work, supporting those who may otherwise be disadvantaged through age, ability, gender, or other characteristics. However, to maximise the benefits, employers must overcome negative attitudes toward, and a lack of confidence in, the technology, and must take steps to reduce errors arising from misuse. This study explores how dynamic graphical signage could be employed to address these issues in a manufacturing task. Forty employees from one UK manufacturing company participated in a field experiment to complete a precision pick-and-place task working in conjunction with a collaborative robotic arm. Twenty-one participants completed the task with the support of dynamic graphical signage that provided information about the robot and the activity, while the rest completed the same task with no signage. The presence of the signage improved the completion time of the task as well as reducing negative attitudes towards the robots. Furthermore, participants provided with no signage had worse outcome expectancies as a function of their response time. Our results indicate that the provision of instructional information conveyed through appropriate graphical signage can improve task efficiency and user wellbeing, contributing to greater workforce sustainability. The findings will be of interest for companies introducing collaborative robots as well as those wanting to improve their workforce wellbeing and technology acceptance.
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    A head mounted augmented reality design practice for maintenance assembly: toward meeting perceptual and cognitive needs of AR users
    (Elsevier, 2021-09-28) Ariansyah, Dedy; Erkoyuncu, John Ahmet; Eimontaite, Iveta; Johnson, Teegan; Oostveen, Anne-Marie; Fletcher, Sarah; Sharples, Sarah
    Head Mounted Display (HMD) based Augmented Reality (AR) is being increasingly used in manufacturing and maintenance. However, limited research has been done to understand user interaction with AR interfaces, which may lead to poor usability, risk of occupational hazards, and low acceptance of AR systems. This paper uses a theoretically-driven approach to interaction design to investigate the impact of different AR modalities in terms of information mode (i.e. video vs. 3D animation) and interaction modality (i.e. hand-gesture vs. voice command) on user performance, workload, eye gaze behaviours, and usability during a maintenance assembly task. The results show that different information modes have distinct impacts compared to paper-based maintenance, in particular, 3D animation led to a 14% improvement over the video instructions in task completion time. Moreover, insights from eye gaze behaviours such as number of fixations and transition between Areas of Interest (AOIs) revealed the differences in attention switching and task comprehension difficulty with the choice of AR modalities. While, subjective user perceptions highlight some ergonomic issues such as misguidance and overreliance, which must be considered and addressed from the joint cognitive systems’ (JCSs) perspective and in line with the predictions derived from the Multiple Resources Model.
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    The social triad model: considering the deployer in a novel approach to trust in human–robot interaction
    (Springer, 2023-09-13) Cameron, David; Collins, Emily C.; de Saille, Stevienna; Eimontaite, Iveta; Greenwood, Alice; Law, James
    There is an increasing interest in considering, measuring, and implementing trust in human-robot interaction (HRI). New avenues in this field include identifying social means for robots to influence trust, and identifying social aspects of trust such as a perceptions of robots’ integrity, sincerity or even benevolence. However, questions remain regarding robots’ authenticity in obtaining trust through social means and their capacity to increase such experiences through social interaction with users. We propose that the dyadic model of HRI misses a key complexity: a robot’s trustworthiness may be contingent on the user’s relationship with, and opinion of, the individual or organisation deploying the robot (termed here, Deployer). We present a case study in three parts on researching HRI and a LEGO® Serious® Play focus group on care robotics to indicate how Users’ trust towards the Deployer can affect trust towards robots and robotic research. Our Social Triad model (User, Robot, Deployer) offers novel avenues for exploring trust in a social context.
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    “We don’t need ergonomics anymore, we need psychology!” – The human analysis needed for human-robot collaboration
    (AHFE International, 2022-07-24) Fletcher, Sarah; Eimontaite, Iveta; Webb, Phil; Lohse, Niels
    Human labour has always been essential in manufacturing and, still, no machine or robot can replace innate human complex physical (dexterity) and cognitive (reasoning) skills. Understandably, industry has constantly sought new automation technologies and largely only concerned itself with physical health and safety issues to improve / maintain production processes, but these industrial engineering approaches have largely overshadowed our understanding of wider social and emotional issues that can also significantly impact on human-system performance and wellbeing. In the current climate, industrial automation is rapidly increasing and crucial to manufacturing competitiveness, and requires greater, closer human interaction. Consequently, people’s cognitive-affective abilities have never been more critical and there has never been a more important time to thoroughly understand them. Moreover, industrial engineers are themselves now more aware and interested in understanding how people can better perform tasks in collaboration with intelligent automation and robotics. This paper describes why industry is only now realising the need for psychology, how far research has advanced our knowledge, and how a major UK project is working to develop new human behaviour models to improve effectiveness in the design of human-robot interactions in modern production processes. As one recent anecdotal comment from a UK industrialist set out: “we don’t need ergonomics anymore – our industrial engineers can do that, we need psychology”!
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    Workplace 4.0: exploring the implications of technology adoption in digital manufacturing on a sustainable workforce
    (MDPI, 2022-03-11) Leesakul, Natalie; Oostveen, Anne-Marie; Eimontaite, Iveta; Wilson, Max L.; Hyde, Richard
    As part of the Industry 4.0 movement, the introduction of digital manufacturing technologies (DMTs) poses various concerns, particularly the impact of technology adoption on the workforce. In consideration of adoption challenges and implications, various studies explore the topic from the perspective of safety, socio-economic impact, technical readiness, and risk assessment. This paper presents mixed methods research to explore the challenges and acceptance factors of the adoption of human-robot collaboration (HRC) applications and other digital manufacturing technologies from the perspective of different stakeholders: from manufacturing employees at all levels to legal experts to consultants to ethicists. We found that some of the prominent challenges and tensions inherent in technology adoption are job displacement, employee’s acceptance, trust, and privacy. This paper argues that it is crucial to understand the wider human factors implications to better strategize technology adoption; therefore, it recommends interventions targeted at individual employees and at the organisational level. This paper contributes to the roadmap of responsible DMT and HRC implementation to encourage a sustainable workforce in digital manufacturing.