A scalable information theoretic approach to distributed robot coordination
This paper presents a scalable information theoretic approach to infer the state of an environment by distributively controlling robots equipped with sensors. The robots iteratively estimate the environment state using a recursive Bayesian filter, while continuously moving to improve the quality of...
Main Authors: | Julian, Brian J., Angermann, Michael, Schwager, Mac, Rus, Daniela |
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Other Authors: | Lincoln Laboratory |
Format: | Article |
Language: | English |
Published: |
IEEE
2021
|
Online Access: | https://hdl.handle.net/1721.1/137084 |
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