CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 深度强化学习
Deep reinforcement learning based automatic exploration for navigation in unknown environment
Li Haoran1,2; Zhang Qichao1,2; Zhao Dongbin1,2
Source PublicationIEEE Transactions on Neural Network and Learning Systems
2019
Issueearly acessPages:1-13
Abstract

This paper investigates the automatic exploration problem under the unknown environment, which is the key point of applying the robotic system to some social tasks. The solution to this problem via stacking decision rules is impossible to cover various environments and sensor properties. Learning-based control methods are adaptive for these scenarios. However, these methods are damaged by low learning efficiency and awkward transferability from simulation to reality. In this paper, we construct a general exploration framework via decomposing the exploration process into the decision, planning, and mapping modules, which increases the modularity of the robotic system. Based on this framework, we propose a deep reinforcement learning-based decision algorithm that uses a deep neural network to learning exploration strategy from the partial map. The results show that this proposed algorithm has better learning efficiency and adaptability for unknown environments. In addition, we conduct the experiments on the physical robot, and the results suggest that the learned policy can be well transferred from simulation to the real robot.

KeywordAutomatic Exploration Deep Reinforcement Learning Optimal Decision Partial Observation
DOIDOI:10.1109/TNNLS.2019.2927869
Indexed BySCI
Language英语
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/26138
Collection复杂系统管理与控制国家重点实验室_深度强化学习
Affiliation1.Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences, Chinese Academy of Sciences
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Li Haoran,Zhang Qichao,Zhao Dongbin. Deep reinforcement learning based automatic exploration for navigation in unknown environment[J]. IEEE Transactions on Neural Network and Learning Systems,2019(early acess):1-13.
APA Li Haoran,Zhang Qichao,&Zhao Dongbin.(2019).Deep reinforcement learning based automatic exploration for navigation in unknown environment.IEEE Transactions on Neural Network and Learning Systems(early acess),1-13.
MLA Li Haoran,et al."Deep reinforcement learning based automatic exploration for navigation in unknown environment".IEEE Transactions on Neural Network and Learning Systems .early acess(2019):1-13.
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