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Human-Automation Collaboration




Faculty Members
Dr. Lydia Tapia
 
Graduate Students
Torin Adamson
Lewis Chiang
 
Undergraduate Students
Valuable Sheffey
 
Collaborators
Dr. Patrick Kelley
Dr. Meeko Oishi
Daniel Gomez
Laura Patrizi
 
Related Projects
Moving Obstacle Avoidance

Automation systems that can find collision-free paths in uncertain environments with dynamic obstacles have highly significant applications, including aerial navigation, satellite coordination, and self-driving cars. However, many of these systems require human monitoring for special cases the automation can not handle. For these cases, an optimal experience results from effective collaboration between the human and automation. Our research focuses on finding ways to adapt technologies for successful human-automation collaboration.



For this purpose, we have developed Busy Beeway. Busy Beeway is a mobile game in which the player must guide the bee avatar, Beelinda, to a goal while avoiding stochastic obstacles (usually wasps). Depending on the mode, the player may complete a level solely or with varying levels of automation guidance. Automation methods are derived from our Moving Obstacle Avoidance Project.


Busy Beeway





Through user studies of Busy Beeway, we seek to answer questions such as:
  • How much is the human willing to rely on the automation?
  • What game states cause the human to take control?
  • What are effective mechanisms for conveying the guidance (including uncertainty) information to the player?


Demo





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Department of Computer Science,
1 University of New Mexico,
Albuquerque, NM 87131-0001 USA 
     Phone 505.277.3112     Fax 505.277.6927 


Department of Computer Science and Engineering | School of Engineering | University of New Mexico