Beyond googly eyes: stakeholder perceptions of robots in construction


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Date

2022-12

Publication Type

Journal Article

ETH Bibliography

yes

Citations

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Abstract

The interest in advanced robotic equipment in construction has increased in recent years. However, actual industry adoption lags behind—and fundamental considerations might be at fault. To date, little scholarship in Architecture, Engineering and Construction (AEC) addresses the stakeholder perception of construction robot design. Therefore, we ask, “How do visual attributes of a construction robot influence the perception of AEC stakeholders?” To conduct our study, we performed a bibliometric analysis on a corpus of 59 scholarly research articles, 5 expert interviews and created and pre-validated a robot database of 50 robot pictures classified on their visual attributes of morphology, color and material. As a result, we present a study with 161 construction professionals who judged these robots based on three visual main criteria: ease of use, work task adaptability and risk of job loss. In total, more than 6500 data points are collected and analyzed using binary logistic regression. The five key findings are that construction professionals perceive that: (1) Zoomorphic (animal-like) robots are easier to use than anthropomorphic (human-like) or mechanomorphic (machine-like) robots, (2) Bright robots are easier to use than dark robots, (3) Zoomorphic and anthropomorphic robots are more multifunctional than mechanomorphic robots, (4) Anthropomorphic and mechanomorphic robots are more of a risk to job loss than zoomorphic robots, and (5) Dark robots are more of a risk to job loss than bright ones. These results are important for academics and practitioners that aim to increase the likelihood of positive stakeholder perception of robots in construction. The findings can further help to develop specific user-centered design principles. Such implementation can reduce the risk of construction professionals rejecting future robots when they are introduced at the AEC job site.

Publication status

published

Editor

Book title

Volume

6 (3)

Pages / Article No.

221 - 237

Publisher

Springer

Event

Edition / version

Methods

Software

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Date collected

Date created

Subject

Construction equipment; Robot design; User perception

Organisational unit

09624 - Hall, Daniel M. (ehemalig) / Hall, Daniel M. (former) check_circle
03709 - Kohler, Matthias / Kohler, Matthias check_circle
03708 - Gramazio, Fabio / Gramazio, Fabio check_circle
03356 - Grote, Gudela / Grote, Gudela check_circle
02284 - NFS Digitale Fabrikation / NCCR Digital Fabrication

Notes

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Is referenced by: handle/20.500.11850/704067