Publication | ACM SIGCHI Conference on Human Factors in Computing Systems 2017

WeBuild

Automatically Distributing Assembly Tasks Among Collocated Workers to Improve Coordination

Abstract

WeBuild: Automatically Distributing Assembly Tasks Among Collocated Workers to Improve Coordination

Ailie Fraser, Tovi Grossman, George Fitzmaurice

ACM SIGCHI Conference on Human Factors in Computing Systems 2017

Physical construction and assembly tasks are often carried out by groups of collocated workers, and they can be difficult to coordinate. Group members must spend time deciding how to split up the task, how to assign subtasks to each other, and in what order subtasks should be completed. Informed by an observational study examining group coordination challenges, we built a task distribution system called WeBuild. Our custom algorithm dynamically assigns subtasks to workers in a group, taking into account factors such as the dependencies between subtasks and the skills of each group member. Each worker views personalized step-bystep instructions on a mobile phone, while a dashboard visualizes the entire process. An initial study found that WeBuild reduced the start-up time needed to coordinate and begin a task, and provides direction for future research to build on toward improving group efficiency and coordination for complex tasks.

Download publication

Associated Autodesk Researchers

C. Ailie Fraser

UC San Diego

Tovi Grossman

University of Toronto

View all researchers

Related Resources

Publication

2023

Leveraging Graph Neural Networks for Graph Regression and Effective Enumeration Reduction

Graph-based framework represents aspects of optimal thermal management…

Publication

2005

Towards integrated performance-driven generative design tools

Performance-driven generative design methods are capable of producing…

Publication

2003

Crosstalk in Surface Electromyography of the Proximal Forearm During Gripping Tasks

Electromyographic (EMG) crosstalk was systematically analyzed to…

Publication

2007

A more bio-plausible approach to the evolutionary inference of finite state machines

With resemblance of finite-state machines to some biological…

Get in touch

Something pique your interest? Get in touch if you’d like to learn more about Autodesk Research, our projects, people, and potential collaboration opportunities.

Contact us