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...
| Published in: | Applied Sciences |
|---|---|
| Main Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-03-01
|
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/11/7/2895 |