End-to-end deep reinforcement learning for decentralized task allocation and navigation for a multi-robot system
In this paper, we present a novel deep reinforcement learning (DRL) based method that is used to perform multi-robot task allocation (MRTA) and navigation in an end-to-end fashion. The policy operates in a decentralized manner mapping raw sensor measurements to the robot’s steering commands without...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/95135/1/ZoolHilmiIsmail202_EndtoEndDeepReinforcement.pdf http://eprints.utm.my/id/eprint/95135/ http://dx.doi.org/10.3390/app11072895 |
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