[1]LIANG Shuang,CAO Qixin,WANG Wenshan,et al.An automatic switching method for multiple location components based on reinforcement learning[J].CAAI Transactions on Intelligent Systems,2016,11(2):149-154.[doi:10.11992/tis.201510031]
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An automatic switching method for multiple location components based on reinforcement learning

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 11 Number of periods: 2016 2 Page number: 149-154 Column: 学术论文—机器学习 Public date: 2016-04-25
Title:
An automatic switching method for multiple location components based on reinforcement learning
Author(s):
LIANG Shuang1;  CAO Qixin1;  WANG Wenshan1;  ZOU Fengshan2
1. Research Institute of Robotics, Shanghai Jiaotong University, Shanghai 200240, China;
2. SIASUN Robot and Automation CO., LTD, Shenyang 110000, China
Keywords:
mobile robot; location; reinforcement learning; middleware; Monte Carlo; multi-sensor; modularization; distributed system
CLC:
TP242.6
DOI:
10.11992/tis.201510031
Abstract:
To address the limitations of location sensors in large-scale dynamic environments, an automatic switching method for multiple robotic components based on reinforcement learning is proposed. This system uses distributed architecture and encapsulates different location sensors and methods into different middleware components. Reinforcement learning is employed to find the optimal strategy for deciding how to switch between components in real time. The simulation result shows that this method can solve problems that a single location method cannot in a large-scale environment and can provide reliable location information depending on multiple location components. This method can also effectively reduce the time delay compared with a method that first traverses all the components directly and then switches components.
References:
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