A Hierarchical Behavioral Dynamic Approach for Naturally Adaptive Human-Agent Pick-and-Place Interactions
Interactive or collaborative pick-and-place tasks occur during all kinds of daily activities, for example, when two or more individuals pass plates, glasses, and utensils back and forth between each other when setting a dinner table or loading a dishwasher together. In the near future, participation...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2019/5964632 |
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| _version_ | 1832556837478596608 |
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| author | Maurice Lamb Patrick Nalepka Rachel W. Kallen Tamara Lorenz Steven J. Harrison Ali A. Minai Michael J. Richardson |
| author_facet | Maurice Lamb Patrick Nalepka Rachel W. Kallen Tamara Lorenz Steven J. Harrison Ali A. Minai Michael J. Richardson |
| author_sort | Maurice Lamb |
| collection | DOAJ |
| description | Interactive or collaborative pick-and-place tasks occur during all kinds of daily activities, for example, when two or more individuals pass plates, glasses, and utensils back and forth between each other when setting a dinner table or loading a dishwasher together. In the near future, participation in these collaborative pick-and-place tasks could also include robotic assistants. However, for human-machine and human-robot interactions, interactive pick-and-place tasks present a unique set of challenges. A key challenge is that high-level task-representational algorithms and preplanned action or motor programs quickly become intractable, even for simple interaction scenarios. Here we address this challenge by introducing a bioinspired behavioral dynamic model of free-flowing cooperative pick-and-place behaviors based on low-dimensional dynamical movement primitives and nonlinear action selection functions. Further, we demonstrate that this model can be successfully implemented as an artificial agent control architecture to produce effective and robust human-like behavior during human-agent interactions. Participants were unable to explicitly detect whether they were working with an artificial (model controlled) agent or another human-coactor, further illustrating the potential effectiveness of the proposed modeling approach for developing systems of robust real/embodied human-robot interaction more generally. |
| format | Article |
| id | doaj-art-9abf9abefec34fdeb74df341020cbd80 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-9abf9abefec34fdeb74df341020cbd802025-02-03T05:44:17ZengWileyComplexity1076-27871099-05262019-01-01201910.1155/2019/59646325964632A Hierarchical Behavioral Dynamic Approach for Naturally Adaptive Human-Agent Pick-and-Place InteractionsMaurice Lamb0Patrick Nalepka1Rachel W. Kallen2Tamara Lorenz3Steven J. Harrison4Ali A. Minai5Michael J. Richardson6School of Informatics, University of Skövde, SwedenDepartment of Psychology, Center for Elite Performance, Expertise and Training, Macquarie University, AustraliaDepartment of Psychology, Center for Elite Performance, Expertise and Training, Macquarie University, AustraliaCenter for Cognition, Action and Perception, Department of Psychology, University of Cincinnati, USADepartment of Kinesiology, University of Connecticut, USADepartment of Electrical Engineering and Computer Science, University of Cincinnati, USADepartment of Psychology, Center for Elite Performance, Expertise and Training, Macquarie University, AustraliaInteractive or collaborative pick-and-place tasks occur during all kinds of daily activities, for example, when two or more individuals pass plates, glasses, and utensils back and forth between each other when setting a dinner table or loading a dishwasher together. In the near future, participation in these collaborative pick-and-place tasks could also include robotic assistants. However, for human-machine and human-robot interactions, interactive pick-and-place tasks present a unique set of challenges. A key challenge is that high-level task-representational algorithms and preplanned action or motor programs quickly become intractable, even for simple interaction scenarios. Here we address this challenge by introducing a bioinspired behavioral dynamic model of free-flowing cooperative pick-and-place behaviors based on low-dimensional dynamical movement primitives and nonlinear action selection functions. Further, we demonstrate that this model can be successfully implemented as an artificial agent control architecture to produce effective and robust human-like behavior during human-agent interactions. Participants were unable to explicitly detect whether they were working with an artificial (model controlled) agent or another human-coactor, further illustrating the potential effectiveness of the proposed modeling approach for developing systems of robust real/embodied human-robot interaction more generally.http://dx.doi.org/10.1155/2019/5964632 |
| spellingShingle | Maurice Lamb Patrick Nalepka Rachel W. Kallen Tamara Lorenz Steven J. Harrison Ali A. Minai Michael J. Richardson A Hierarchical Behavioral Dynamic Approach for Naturally Adaptive Human-Agent Pick-and-Place Interactions Complexity |
| title | A Hierarchical Behavioral Dynamic Approach for Naturally Adaptive Human-Agent Pick-and-Place Interactions |
| title_full | A Hierarchical Behavioral Dynamic Approach for Naturally Adaptive Human-Agent Pick-and-Place Interactions |
| title_fullStr | A Hierarchical Behavioral Dynamic Approach for Naturally Adaptive Human-Agent Pick-and-Place Interactions |
| title_full_unstemmed | A Hierarchical Behavioral Dynamic Approach for Naturally Adaptive Human-Agent Pick-and-Place Interactions |
| title_short | A Hierarchical Behavioral Dynamic Approach for Naturally Adaptive Human-Agent Pick-and-Place Interactions |
| title_sort | hierarchical behavioral dynamic approach for naturally adaptive human agent pick and place interactions |
| url | http://dx.doi.org/10.1155/2019/5964632 |
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