Robot Path Planning in Uncertain Environments: A Language-Measure-Theoretic Approach
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Published:2014-10-21
Issue:3
Volume:137
Page:
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ISSN:0022-0434
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Container-title:Journal of Dynamic Systems, Measurement, and Control
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language:en
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Short-container-title:
Author:
Jha Devesh K.1, Li Yue1, Wettergren Thomas A.21, Ray Asok3
Affiliation:
1. Mechanical & Nuclear Engineering Department Pennsylvania State University, University Park, PA 16802 e-mail: 2. Naval Undersea Warfare Center, Newport, RI 02841; 3. Fellow ASME Mechanical & Nuclear Engineering Department Pennsylvania State University, University Park, PA 16802 e-mail:
Abstract
This paper addresses the problem of goal-directed robot path planning in the presence of uncertainties that are induced by bounded environmental disturbances and actuation errors. The offline infinite-horizon optimal plan is locally updated by online finite-horizon adaptive replanning upon observation of unexpected events (e.g., detection of unanticipated obstacles). The underlying theory is developed as an extension of a grid-based path planning algorithm, called ν⋆, which was formulated in the framework of probabilistic finite state automata (PFSA) and language measure from a control-theoretic perspective. The proposed concept has been validated on a simulation test bed that is constructed upon a model of typical autonomous underwater vehicles (AUVs) in the presence of uncertainties.
Publisher
ASME International
Subject
Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering
Reference18 articles.
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