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1. Measuring Risk Attitudes for Strategic Decision-Making in a Collaborative Engineering Design Process

   Avşar, Alkim Z.; Stern, Jordan L.; Grogan, Paul T. (August 2022, ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference)

   This paper evaluates a questionnaire-based risk attitude assessment method to quantify individual risk attitudes for strategic, multi-actor design decisions. A lottery-equivalence questionnaire elicits a utility curve for risky payoffs which is fit to a Constant Absolute Risk Aversion (CARA) model. Secondary data from a multi-actor design experiment provides observations of strategic decisions in two-actor design games for validation. 124 participants complete the risk attitude questionnaire and a series of 29 experimental tasks. Assuming participants follow the risk dominance equilibrium selection criterion, a risk-neutral utility function accurately predicts 62.2% of decisions. Incorporating risk attitudes elicited from the questionnaire only increases the accuracy to 63.3% while incorporating risk attitudes inferred from observations increases the accuracy to 77.5%. While participants exhibit differential risk attitudes in design tasks, results show the lottery-equivalent questionnaire does not provide risk attitudes consistent with strategic design decisions. Results support findings that risk in the engineering domain is contextual. This paper concludes that risk attitude is an important factor in understanding strategic decisions in interactive engineering design settings and understanding risk attitudes can help create more efficient design processes. 

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2. The Impact of Engineering Information Formats on Workers’ Cognitive Load in Working Memory Development

   Shi, Y. (June 2020, Construction Research Congress 2020)

   Owing to the increasing dynamics and complexity of construction tasks, workers often need to memorize a big amount of engineering information prior to the operations, such as spatial orientations and operational procedures. The working memory development, as a result, is critical to the performance and safety of many construction tasks. This study investigates how the format of engineering information affects human working memory based on a human-subject Virtual Reality (VR) experiment (n=90). A VR model was created to simulate a pipe maintenance task. First, participants were asked to review the task procedures in one of the following formats, including 2D isometric drawings, 3D model, and VR model. After the review session, participants were asked to perform the pipe maintenance task in the virtual environment based on their working memory. The operation accuracy and time were used as the key performance indicators of the working memory development. The experiment results indicate that the 3D and VR groups outperformed the 2D group in both operation accuracy and time, suggesting that a more immersive instruction leads to a better working memory. A further examination finds that the 2D group presented a significantly higher level of intrinsic cognitive load and extraneous cognitive load in the working memory development compared to the 3D and VR groups, indicating that different engineering information formats can cause different levels of cognitive load in working memory development, and ultimately affect the final performance. The findings are expected to inspire the design of intelligent information systems that adapt to the cognitive load of construction workers for improved working memory development. 

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3. Sensory manipulation as a countermeasure to robot teleoperation delays: system and evidence

   https://doi.org/10.1038/s41598-024-54734-1  

   Du, Jing; Vann, William; Zhou, Tianyu; Ye, Yang; Zhu, Qi (February 2024, Scientific Reports)

   Abstract In the realm of robotics and automation, robot teleoperation, which facilitates human–machine interaction in distant or hazardous settings, has surged in significance. A persistent issue in this domain is the delays between command issuance and action execution, causing negative repercussions on operator situational awareness, performance, and cognitive load. These delays, particularly in long-distance operations, are difficult to mitigate even with the most advanced computing advancements. Current solutions mainly revolve around machine-based adjustments to combat these delays. However, a notable lacuna remains in harnessing human perceptions for an enhanced subjective teleoperation experience. This paper introduces a novel approach of sensory manipulation for induced human adaptation in delayed teleoperation. Drawing from motor learning and rehabilitation principles, it is posited that strategic sensory manipulation, via altered sensory stimuli, can mitigate the subjective feeling of these delays. The focus is not on introducing new skills or adapting to novel conditions; rather, it leverages prior motor coordination experience in the context of delays. The objective is to reduce the need for extensive training or sophisticated automation designs. A human-centered experiment involving 41 participants was conducted to examine the effects of modified haptic cues in teleoperations with delays. These cues were generated from high-fidelity physics engines using parameters from robot-end sensors or physics engine simulations. The results underscored several benefits, notably the considerable reduction in task time and enhanced user perceptions about visual delays. Real-time haptic feedback, or the anchoring method, emerged as a significant contributor to these benefits, showcasing reduced cognitive load, bolstered self-confidence, and minimized frustration. Beyond the prevalent methods of automation design and training, this research underscores induced human adaptation as a pivotal avenue in robot teleoperation. It seeks to enhance teleoperation efficacy through rapid human adaptation, offering insights beyond just optimizing robotic systems for delay compensations. 

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4. The strategy dynamics of collective systems: Underlying hindrances beyond two-actor coordination

   https://doi.org/10.1371/journal.pone.0301394  

   Valencia-Romero, Ambrosio; Grogan, Paul T (April 2024, PLOS ONE)

   Feng, Minyu (Ed.)

   Engineering systems, characterized by their high technical complexity and societal intricacies, require a strategic design approach to navigate multifaceted challenges. Understanding the circumstances that affect strategic action in these systems is crucial for managing complex real-world challenges. These challenges go beyond localized coordination issues and encompass intricate dynamics, requiring a deep understanding of the underlying structures impacting strategic behaviors, the interactions between subsystems, and the conflicting needs and expectations of diverse actors. Traditional optimization and game-theoretic approaches to guide individual and collective decisions need adaptation to capture the complexities of these design ecosystems, particularly in the face of increasing numbers of decision-makers and various interconnections between them. This paper presents a framework for studying strategic decision-making processes in collective systems. It tackles the combinatorial complexity and interdependencies inherent in large-scale systems by representing strategic decision-making processes as binary normal-form games, then dissects and reinterprets them in terms of multiple compact games characterized by two real-numbered structural factors and classifies them across four strategy dynamical domains associated with different stability conditions. We provide a mathematical characterization and visual representation of emergent strategy dynamics in games with three or more actors intended to facilitate its implementation by researchers and practitioners and elicit new perspectives on design and management for optimizing systems-of-systems performance. We conclude this paper with a discussion of the opportunities and challenges of adopting this framework within and beyond the context of engineering systems. 

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5. The Impact of Robotics Expertise on Iterative Robot Design Decisions and Vulnerability to Design Fixation

   https://doi.org/10.1115/DETC2023-116874  

   Wilson, Cristina G.; Brown, Kallahan; Sung, Cynthia (August 2023, ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE))

   Robot design is a complex cognitive activity that requires the designer to iteratively navigate multiple engineering disciplines and the relations between them. In this paper, we explore how people approach robot design and how trends in design strategy vary with the level of expertise of the designer. Using our interactive Build-a-Bot software tool, we recruited 39 participants from the 2022 IEEE International Conference on Robotics and Automation. These participants varied in age from 19 to 56 years, and had between 0 and 17 years of robotics experience. We tracked the participants’ design decisions over the course of a 15 min. task of designing a ground robot to cross an uneven environment. Our results showed that participants engaged in iterative testing and modification of their designs, but unlike previous studies, there was no statistically significant effect of participant’s expertise on the frequency of iterations. We additionally found that, across levels of expertise, participants were vulnerable to design fixation, in which they latched onto an initial design concept and insufficiently adjusted the design, even when confronted with difficulties developing the concept into a satisfactory solution. The results raise interesting questions for how future engineers can avoid fixation and how design tools can assist in both efficient assessment and optimization of design workflow for complex design tasks. 

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