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Simultaneous Planning and Action: Neural-dynamic Sequencing of Elementary Behaviors in Robot Navigation
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Interaction Lab)ORCID iD: 0000-0002-6568-9342
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. Department of Applied IT, University of Gothenburg, Sweden. (Interaction Lab)
Institute of Neuroinformatics, University of Zurich and ETH Zurich, Switzerland.
2015 (English)In: Adaptive Behavior, ISSN 1059-7123, E-ISSN 1741-2633, Vol. 23, no 5, 243-264 p.Article in journal (Refereed) Published
Abstract [en]

A technique for Simultaneous Planning and Action (SPA) based on Dynamic Field Theory (DFT) is presented. The model builds on previous workon representation of sequential behavior as attractors in dynamic neural fields. Here, we demonstrate how chains of competing attractors can be used to represent dynamic plans towards a goal state. The presentwork can be seen as an addition to a growing body of work that demonstratesthe role of DFT as a bridge between low-level reactive approachesand high-level symbol processing mechanisms. The architecture is evaluatedon a set of planning problems using a simulated e-puck robot, including analysis of the system's behavior in response to noise and temporary blockages ofthe planned route. The system makes no explicit distinction betweenplanning and execution phases, allowing continuous adaptation of the planned path. The proposed architecture exploits the DFT property of stability in relation to noise and changes in the environment. The neural dynamics are also exploited such that stay-or-switch action selection emerges where blockage of a planned path occurs: stay until the transient blockage is removed versus switch to an alternative route to the goal.

Place, publisher, year, edition, pages
Sage Publications, 2015. Vol. 23, no 5, 243-264 p.
Keyword [en]
Dynamic field theory, goal directed behavior, simultaneous planning and action
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Research subject
URN: urn:nbn:se:his:diva-11565DOI: 10.1177/1059712315601188ISI: 000362888100001ScopusID: 2-s2.0-84944450587OAI: diva2:860930
Neural Dynamics, 7:th framework of the EU, #270247
EU, FP7, Seventh Framework Programme, 270247
Available from: 2015-10-14 Created: 2015-09-25 Last updated: 2016-02-19Bibliographically approved

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