The impact of human-robot interface design on the use of a learning robot system

Guillaume Doisy, Joachim Meyer, Yael Edan

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


There is limited knowledge on how to design effective interfaces to enable nonexpert users to interact with robot learning algorithms. This paper focuses on an interface design challenge: How to provide the user with sufficient information about the learned behavior. A simulated robotic task where the robot has online learning capabilities was developed. This platform was used to study the impact of the variability of the environmental conditions, the information provided on the relation between the learned robot behavior and the conditions in the environment, and the presence of a preview of the learned robot behavior on the use of the system and on task performance. The results show significant effects of the type and the quantity of displayed information. Forty-two participants made the best use of brief and contextualized notifications about changes in the environment: their presence improved the overall performance and the usage of the automation and reduced the workload. In contrast, adding previews of the learned behavior surprisingly impaired performance and reduced the use of automation.

Original languageEnglish
Article number6863710
Pages (from-to)788-795
Number of pages8
JournalIEEE Transactions on Human-Machine Systems
Issue number6
StatePublished - 1 Dec 2014


  • Human - robot interaction
  • Human factors
  • interface design
  • robot learning
  • service robots
  • user interfaces

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Control and Systems Engineering
  • Signal Processing
  • Human-Computer Interaction
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence


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