NDLI: HTN robot planning in partially observable dynamic environments

Content Provider	IEEE Xplore Digital Library
Author	Weser, M. Off, D. Jianwei Zhang
Copyright Year	2010
Description	Author affiliation: TAMS, Department of Informatics, Hamburg University, Vogt-Kölln-Strasse 30, 22527, Germany (Weser, M.; Off, D.; Jianwei Zhang)
Abstract	Experiments showed that Hierarchical Task Network (HTN) planners are suitable to find solutions for nontrivial tasks in complex scenarios. Mobile service robots are able to execute actions which may constitute the basic building blocks to achieve high-level goals. However, only few experiments demonstrate the application of a general purpose deliberative planner in the domain of mobile service robots. One challenging problem arises from the fact that adaptive AI-based planners presume the closed-world assumption (CWA) and are therefore unable to deal with incomplete information. Unknown objects which are not represented in the planning domain, for example, cannot be integrated into the planning process. Since mobile service robots act in a real dynamic environment and construct or adapt their world model autonomously based on sensory data, they are inevitably confronted with uncertain and incomplete information about the world. This conflict between simplified assumptions for planning on the one hand and the complexity of the real world on the other constitutes a major problem of modern robotics. This paper describes two approaches to dealing with incomplete world knowledge in the context of HTN robot planning. Several experiments demonstrate that the approaches can successfully be applied in a dynamic and unstructured environment.
Starting Page	1505
Ending Page	1510
File Size	1719460
Page Count	6
File Format	PDF
ISBN	9781424450381
ISSN	10504729
DOI	10.1109/ROBOT.2010.5509770
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Service robots Robot sensing systems Robot control Mobile robots Robotics and automation Process planning Observability USA Councils Informatics Control systems
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

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