Supportive actions for manipulation in human-robot coworker teams

Shray Bansal, Rhys Newbury, Wesley P. Chan, Akansel Cosgun, Aimee Allen, Dana Kulic, Tom W. Drummond, Charles Isbell

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

The increasing presence of robots alongside humans, such as in human-robot teams in manufacturing, gives rise to research questions about the kind of behaviors people prefer in their robot counterparts. We term actions that support interaction by reducing future interference with others as supportive robot actions and investigate their utility in a co-located manipulation scenario. We compare two robot modes in a shared table pick-and-place task: (1) Task-oriented: the robot only takes actions to further its task objective and (2) Supportive: the robot sometimes prefers supportive actions to task-oriented ones when they reduce future goal-conflicts. Our experiments in simulation, using a simplified human model, reveal that supportive actions reduce the interference between agents, especially in more difficult tasks, but also cause the robot to take longer to complete the task. We implemented these modes on a physical robot in a user study where a human and a robot perform object placement on a shared table. Our results show that a supportive robot was perceived more favorably as a coworker and also reduced interference with the human in one of two scenarios. However, it also took longer to complete the task highlighting an interesting trade-off between task-efficiency and human-preference that needs to be considered before designing robot behavior for close-proximity manipulation scenarios.
Original languageEnglish
Title of host publication2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)2020 IEEE International Conference on Intelligent Robots and Systems
EditorsMarcia O’Malley
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages11261-11267
Number of pages7
ISBN (Electronic)9781728162126
ISBN (Print)9781728162133
DOIs
Publication statusPublished - 2020
EventIEEE/RSJ International Conference on Intelligent Robots and Systems 2020 - Virtual, Las Vegas, United States of America
Duration: 24 Jan 202124 Jan 2021
https://ieeexplore-ieee-org.ezproxy.lib.monash.edu.au/xpl/conhome/9340668/proceeding
https://www.iros2020.org (Website)

Publication series

Name2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
PublisherIEEE, Institute of Eelctrical and Electronic Engineers Inc.
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

ConferenceIEEE/RSJ International Conference on Intelligent Robots and Systems 2020
Abbreviated titleIROS 2020
CountryUnited States of America
CityLas Vegas
Period24/01/2124/01/21
Internet address

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