Semantic-level decentralized multi-robot decision-making using probabilistic macro-observations

Semantic-level decentralized multi-robot decision-making using probabilistic macro-observations

Robust environment perception is essential for decision-making on robots operating in complex domains. Intelligent task execution requires principled treatment of uncertainty sources in a robot's observation model. This is important not only for low-level observations (e.g., accelerom-eter data...

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Bibliographic Details
Main Authors: Amato, Christopher (Author), Vian, John (Author), Omidshafiei, Shayegan (Contributor), Liu, Shih-Yuan (Contributor), Everett, Michael F (Contributor), Lopez, Brett Thomas (Contributor), Liu, Miao (Contributor), How, Jonathan P (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Department of Mechanical Engineering (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2018-04-13T21:42:25Z.
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Online Access:Get fulltext

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