Long-run multi-robot planning under uncertain action durations for persistent tasks

Long-run multi-robot planning under uncertain action durations for persistent tasks

This paper presents an approach for multi-robot long-term planning under uncertainty over the duration of actions. The proposed methodology takes advantage of generalized stochastic Petri nets with rewards (GSPNR) to model multi-robot problems. A GSPNR allows for unified modeling of action selection...

書誌詳細
主要な著者:	Azevedo, C, Lacerda, B, Hawes, N, Lima, P
フォーマット:	Conference item
言語:	English
出版事項:	IEEE 2021

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