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It Gets Worse Before it Gets Better: Timing of Instructions in Close Human-Robot Collaboration

Published: 06 March 2017 Publication History

Abstract

A micro-analysis of the timing of people's actions in close human-robot collaborations shows that people expect robots to attend to interactional achievements in the same way as humans do; that is, they expect that in a repeated task, the robot builds on the common ground acquired in the previous interaction. This expectation is revealed through increased response times by the human users, which leads to less fluent interactions; however, users recover over the course of the next actions, orienting at the principle of least collaborative effort. The paper thus illustrates a) how a qualitative microanalysis provides a methodological tool for uncovering users' expectations online (in comparison to post hoc by means of questionnaires, for instance), and b) what exactly it is that users expect.

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Cited By

View all
  • (2022)Perceptions of the Helpfulness of Unexpected Agent AssistanceProceedings of the 10th International Conference on Human-Agent Interaction10.1145/3527188.3561915(41-50)Online publication date: 5-Dec-2022
  • (2020)Towards Effective Interface Designs for Collaborative HRI in ManufacturingACM Transactions on Human-Robot Interaction10.1145/33850099:4(1-55)Online publication date: 31-May-2020
  • (2020)Integrative Social Robotics Hands-onInteraction Studies. Social Behaviour and Communication in Biological and Artificial SystemsInteraction Studies / Social Behaviour and Communication in Biological and Artificial SystemsInteraction Studies10.1075/is.18058.fis21:1(145-185)Online publication date: 24-Jan-2020
  • Show More Cited By

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  1. It Gets Worse Before it Gets Better: Timing of Instructions in Close Human-Robot Collaboration

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          cover image ACM Conferences
          HRI '17: Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction
          March 2017
          462 pages
          ISBN:9781450348850
          DOI:10.1145/3029798
          Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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          Publication History

          Published: 06 March 2017

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          Author Tags

          1. common ground
          2. contingency
          3. human-robot collaboration
          4. timing
          5. uncanny valley

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          HRI '17 Paper Acceptance Rate 51 of 211 submissions, 24%;
          Overall Acceptance Rate 192 of 519 submissions, 37%

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          Cited By

          View all
          • (2022)Perceptions of the Helpfulness of Unexpected Agent AssistanceProceedings of the 10th International Conference on Human-Agent Interaction10.1145/3527188.3561915(41-50)Online publication date: 5-Dec-2022
          • (2020)Towards Effective Interface Designs for Collaborative HRI in ManufacturingACM Transactions on Human-Robot Interaction10.1145/33850099:4(1-55)Online publication date: 31-May-2020
          • (2020)Integrative Social Robotics Hands-onInteraction Studies. Social Behaviour and Communication in Biological and Artificial SystemsInteraction Studies / Social Behaviour and Communication in Biological and Artificial SystemsInteraction Studies10.1075/is.18058.fis21:1(145-185)Online publication date: 24-Jan-2020
          • (2018)Learning Semantics of Gestural Instructions for Human-Robot CollaborationFrontiers in Neurorobotics10.3389/fnbot.2018.0000712Online publication date: 19-Mar-2018
          • (2017)Proactive, incremental learning of gesture-action associations for human-robot collaboration2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)10.1109/ROMAN.2017.8172325(346-353)Online publication date: 28-Aug-2017
          • (2017)Supervised Learning of Gesture-Action Associations for Human-Robot Collaboration2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017)10.1109/FG.2017.97(778-783)Online publication date: 30-May-2017

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