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Abstract: We present the Robel supervision system which is able to learn from experience robust ways to perform high level tasks (such as "navigate to"). Each possible way to perform the task is modeled as an Hierarchical Tasks Network (HTN), called modality whose primitives are sensory-motor functions. An HTN planning process synthesizes all the consistent modalities to achieve a task. The relationship between supervision states and the appropriate modality is learned through experience as a Markov... (Update)
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BibTeX entry: (Update)
Benoit Morisset, Guillaume Infantes, Malik Ghallab, and Felix Ingrand. Robel: Synthesizing and Controlling Complex Robust Robot Behaviors. In 4th International Cognitive Robotics Workshop, Valencia, Spain, August 23-24, 2004. http://citeseer.ist.psu.edu/morisset04robel.html More
@misc{ morisset04robel,
author = "B. Morisset and G. Infantes and M. Ghallab and F. Ingrand",
title = "Robel: Synthesizing and Controlling Complex Robust Robot Behaviors",
text = "Benoit Morisset, Guillaume Infantes, Malik Ghallab, and Felix Ingrand.
Robel: Synthesizing and Controlling Complex Robust Robot Behaviors. In 4th
International Cognitive Robotics Workshop, Valencia, Spain, August 23-24,
2004.",
year = "2004",
url = "citeseer.ist.psu.edu/morisset04robel.html" }
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