Human-Robot Interactive Planning using Cross-Training: A Human Team Training Approach
Robots are increasingly introduced to work in concert with people in high-intensity domains, such as manufacturing, space exploration and hazardous environments. Although there are numerous studies on human teamwork and coordination in these settings, very little prior work exists on applying these...
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| Format: | Article |
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American Institute of Aeronautics and Astronautics (AIAA)
2018
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| Online Access: | http://hdl.handle.net/1721.1/116078 https://orcid.org/0000-0003-1338-8107 |
| _version_ | 1826197096813821952 |
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| author | Nikolaidis, Stefanos Shah, Julie A |
| author2 | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics |
| author_facet | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Nikolaidis, Stefanos Shah, Julie A |
| author_sort | Nikolaidis, Stefanos |
| collection | MIT |
| description | Robots are increasingly introduced to work in concert with people in high-intensity domains, such as manufacturing, space exploration and hazardous environments. Although there are numerous studies on human teamwork and coordination in these settings, very little prior work exists on applying these models to human-robot interaction. In this paper we propose a novel framework for applying prior art in Shared Mental Models (SMMs) to promote effective human-robot teaming. We present a computational teaming model to encode joint action in a human-robot team. We present results from human subject experiments that evaluate human-robot teaming in a virtual environment. We show that cross-training, a common practice used for improving human team shared mental models, yields statistically significant improvements in convergence of the computational teaming model (p=0.02) and in the human participants' perception that the robot performed according to their preferences (p=0.01), as compared to robot training using a standard interactive reinforcement learning approach. © 2012 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved. |
| first_indexed | 2024-09-23T10:42:45Z |
| format | Article |
| id | mit-1721.1/116078 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T10:42:45Z |
| publishDate | 2018 |
| publisher | American Institute of Aeronautics and Astronautics (AIAA) |
| record_format | dspace |
| spelling | mit-1721.1/1160782022-09-30T22:27:15Z Human-Robot Interactive Planning using Cross-Training: A Human Team Training Approach Nikolaidis, Stefanos Shah, Julie A Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Nikolaidis, Stefanos Shah, Julie A Robots are increasingly introduced to work in concert with people in high-intensity domains, such as manufacturing, space exploration and hazardous environments. Although there are numerous studies on human teamwork and coordination in these settings, very little prior work exists on applying these models to human-robot interaction. In this paper we propose a novel framework for applying prior art in Shared Mental Models (SMMs) to promote effective human-robot teaming. We present a computational teaming model to encode joint action in a human-robot team. We present results from human subject experiments that evaluate human-robot teaming in a virtual environment. We show that cross-training, a common practice used for improving human team shared mental models, yields statistically significant improvements in convergence of the computational teaming model (p=0.02) and in the human participants' perception that the robot performed according to their preferences (p=0.01), as compared to robot training using a standard interactive reinforcement learning approach. © 2012 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved. ABB Inc. ABB Corporate Research Center (Vasteras, Sweden) Alexander S. Onassis Public Benefit Foundation 2018-06-05T13:08:04Z 2018-06-05T13:08:04Z 2012-06 2018-04-10T18:03:11Z Article http://purl.org/eprint/type/ConferencePaper 978-1-60086-939-6 http://hdl.handle.net/1721.1/116078 Nikolaidis, Stefanos, and Julie Shah. “Human-Robot Interactive Planning Using Cross-Training: A Human Team Training Approach.” Infotech@Aerospace 2012 (June 19, 2012). https://orcid.org/0000-0003-1338-8107 http://dx.doi.org/10.2514/6.2012-2536 Infotech@Aerospace 2012 Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf American Institute of Aeronautics and Astronautics (AIAA) MIT Web Domain |
| spellingShingle | Nikolaidis, Stefanos Shah, Julie A Human-Robot Interactive Planning using Cross-Training: A Human Team Training Approach |
| title | Human-Robot Interactive Planning using Cross-Training: A Human Team Training Approach |
| title_full | Human-Robot Interactive Planning using Cross-Training: A Human Team Training Approach |
| title_fullStr | Human-Robot Interactive Planning using Cross-Training: A Human Team Training Approach |
| title_full_unstemmed | Human-Robot Interactive Planning using Cross-Training: A Human Team Training Approach |
| title_short | Human-Robot Interactive Planning using Cross-Training: A Human Team Training Approach |
| title_sort | human robot interactive planning using cross training a human team training approach |
| url | http://hdl.handle.net/1721.1/116078 https://orcid.org/0000-0003-1338-8107 |
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