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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Bibliographic Details
Main Authors: Ahmed Elfakharany, Zool Hilmi Ismail
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/11/7/2895