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Finding Ways to Get the Job Done: An Affordance-Based Approach

  • Adapting plans to changes in the environment by finding alternatives and taking advantage of opportunities is a common human behavior. The need for such behavior is often rooted in the uncertainty produced by our incomplete knowledge of the environment. While several existing planning approaches deal with such issues, artificial agents still lack the robustness that humans display in accomplishing their tasks. In this work, we address this brittleness by combining Hierarchical Task Network planning, Description Logics, and the notions of affordances and conceptual similarity. The approach allows a domestic service robot to find ways to get a job done by making substitutions. We show how knowledge is modeled, how the reasoning process is used to create a constrained planning problem, and how the system handles cases where plan generation fails due to missing/unavailable objects. The results of the evaluation for two tasks in a domestic service domain show the viability of the approach in finding and making the appropriate goal transformations.

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Metadaten
Document Type:Conference Object
Language:English
Author:Iman Awaad, Gerhard Kraetzschmar, Joachim Hertzberg
Parent Title (English):ICAPS 2014. 24th International Conference on Automated Planning and Scheduling. New Hampshire, USA, from June 21–26, 2014
First Page:499
Last Page:503
ISBN:978-1-57735-660-8
DOI:https://doi.org/10.1609/icaps.v24i1.13674
Date of first publication:2014/11/05
Copyright:©2014, Association for the Advancement of ArtificialIntelligence (www.aaai.org). All rights reserved
Departments, institutes and facilities:Fachbereich Informatik
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2015/04/02