Autonomous Exploration of Mobile Robots via Deep Reinforcement Learning Based on Spatiotemporal Information on Graph

Autonomous Exploration of Mobile Robots via Deep Reinforcement Learning Based on Spatiotemporal Information on Graph

In this paper, we address the problem of autonomous exploration in unknown environments for ground mobile robots with deep reinforcement learning (DRL). To effectively explore unknown environments, we construct an exploration graph considering historical trajectories, frontier waypoints, landmarks,...

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Bibliographic Details
Main Authors:	Zhiwen Zhang, Chenghao Shi, Pengming Zhu, Zhiwen Zeng, Hui Zhang
Format:	Article
Language:	English
Published:	MDPI AG 2021-09-01
Series:	Applied Sciences
Subjects:	autonomous exploration deep reinforcement learning spatiotemporal information graph convolutional network temporal convolutional network gated recurrent unit
Online Access:	https://www.mdpi.com/2076-3417/11/18/8299

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