Planning to see: A hierarchical approach to planning visual actions on a robot using POMDPs

Flexible, general-purpose robots need to autonomously tailor their sensing and information processing to the task at hand. We pose this challenge as the task of planning under uncertainty. In our domain, the goal is to plan a sequence of visual operators to apply on regions of interest (ROIs) in ima...

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Bibliographic Details
Published in:	Artificial intelligence Vol. 174; no. 11; pp. 704 - 725
Main Authors:	Sridharan, Mohan, Wyatt, Jeremy, Dearden, Richard
Format:	Journal Article
Language:	English
Published:	Oxford Elsevier B.V 01-07-2010 Elsevier
Subjects:	Applied sciences Artificial intelligence Computer science; control theory; systems Control theory. Systems Exact sciences and technology Hierarchical POMDPs Management Mathematical models Operators Pattern recognition. Digital image processing. Computational geometry Probabilistic planning Robotics Robots Tasks Uncertainty Visual Visual processing Hierarchical POMDPs Visual processing Probabilistic planning Robotics Human Markov decision Probabilistic approach Image processing Decision making Sequential decision Modeling Hierarchized structure Hierarchic relation Interest region Cognitive theory Partial observability Uncertain system Information processing Planning Hierarchical system Reliability Execution time
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