[1]王作为,徐征,张汝波,等.记忆神经网络在机器人导航领域的应用与研究进展[J].智能系统学报,2020,15(5):835-846.[doi:10.11992/tis.202002020]
WANG Zuowei,XU Zheng,ZHANG Rubo,et al.Research progress and application of memory neural network in robot navigation[J].CAAI Transactions on Intelligent Systems,2020,15(5):835-846.[doi:10.11992/tis.202002020]
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WANG Zuowei,XU Zheng,ZHANG Rubo,et al.Research progress and application of memory neural network in robot navigation[J].CAAI Transactions on Intelligent Systems,2020,15(5):835-846.[doi:10.11992/tis.202002020]
记忆神经网络在机器人导航领域的应用与研究进展
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
15
期数:
2020年第5期
页码:
835-846
栏目:
综述
出版日期:
2020-09-05
- Title:
- Research progress and application of memory neural network in robot navigation
- Keywords:
- memory neural network; robot navigation; deep reinforcement learning; differentiable neural computer; differentiable neural dictionary; deep learning; reinforcement learning; memory networks
- 分类号:
- TP183
- 文献标志码:
- A
- 摘要:
- 记忆神经网络非常适合解决时间序列决策问题，将其用于机器人导航领域是非常有前景的新兴研究领域。本文主要讨论记忆神经网络在机器人导航领域的研究进展。给出几种基本记忆神经网络结合导航任务的工作机理，总结了不同模型的优缺点；对记忆神经网络在导航领域的研究进展进行简要综述；进一步介绍导航验证环境的发展；最后梳理了记忆神经网络在导航问题所面临的复杂性挑战，并预测了记忆神经网络在导航领域未来的发展方向。
- Abstract:
- Memory networks are a relatively new class of models designed to alleviate the problem of learning long-term dependencies in sequential data, by providing an explicit memory representation for each token in the sequence, and they can be used for learning navigation policies in an unstructured terrain, which is a complex task. Memory neural networks are highly suitable for solving time series decision-making problems, and their application in robot navigation is a very promising and emerging research field. The research progress of memory neural networks in the field of robot navigation is primarily discussed in this paper. First, the working mechanism of several basic memory neural networks used for robot navigationis introduced, and the advantages and disadvantages of different models are summarized. Then, the research progress of memory neural network in navigation field is briefly reviewed, and the development of navigation verification environment is discussed. Finally, the complex challenges faced by memory neural networks in navigation are summarized, and the future development of memory neural networks in navigation field is predicted.
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- 相似文献/References:
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备注/Memo
收稿日期:2020-02-27。
基金项目:国家自然科学基金面上项目（61972456）；天津市教委科研计划项目（2019KJ018）；天津工业大学学位与研究生教育改革项目（Y20180104）
作者简介:王作为,副教授,主要研究方向为智能机器人与智能控制、机器学习与人工智能。主持省部级、局级基金项目3项。发表学术论文20余篇;徐征,副教授,主要研究方向为电机控制与运动控制系统。获天津市科技进步二等奖1项。主持和参与省部级基金项目5项。发表学术论文8篇;张汝波,教授,博士生导师,主要研究方向为智能机器人与智能控制、机器学习与计算智能、智能信息处理。主持完成国防973、国家863、国家自然科学基金项目、省自然科学基金项目和国防预研项目20余项,获国家科学技术进步二等奖1项、国防科学技术奖3项、中国船舶工业总公司科技进步奖2项。发表学术论文200余篇
通讯作者:王作为.E-mail:wangzuowei@126.com
更新日期/Last Update:
2021-01-15