Goal inference improves objective and perceived performance in human-robot collaboration

Chang Liu, Jessica B. Hamrick, Jaime F. Fisac, Anca D. Dragan, J. Karl Hedrick, S. Shankar Sastry, Thomas L. Griffiths

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

The study of human-robot interaction is fundame design and use of robotics in real-world application will need to predict and adapt to the actions of h laborators in order to achieve good performanc prove safety and end-user adoption. This paper e human-robot collaboration scheme that combine allocation and motion levels of reasoning: the rob uses Bayesian inference to predict the next goal man partner from his or her ongoing motion, an its own actions in real time. This anticipative ada desirable in many practical scenarios, where huma able or unwilling to take on the cognitive overhea to explicitly communicate their intent to the rob havioral experiment indicates that the combinati inference and dynamic task planning significantly both objective and perceived performance of th robot team. Participants were highly sensitive ferences between robot behaviors, preferring to w robot that adapted to their actions over one that did not.

Original languageEnglish (US)
Title of host publicationAAMAS 2016 - Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages940-948
Number of pages9
ISBN (Electronic)9781450342391
StatePublished - Jan 1 2016
Externally publishedYes
Event15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016 - Singapore, Singapore
Duration: May 9 2016May 13 2016

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Other

Other15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016
CountrySingapore
CitySingapore
Period5/9/165/13/16

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

Keywords

  • Human-agent interaction
  • Intention collaborative task allocation
  • Teamwork

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  • Cite this

    Liu, C., Hamrick, J. B., Fisac, J. F., Dragan, A. D., Hedrick, J. K., Sastry, S. S., & Griffiths, T. L. (2016). Goal inference improves objective and perceived performance in human-robot collaboration. In AAMAS 2016 - Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems (pp. 940-948). (Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).