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机器人室内语义建图中的场所感知方法综述

朱博 高翔 赵燕喃

朱博, 高翔, 赵燕喃. 机器人室内语义建图中的场所感知方法综述. 自动化学报, 2017, 43(4): 493-508. doi: 10.16383/j.aas.2017.c160350
引用本文: 朱博, 高翔, 赵燕喃. 机器人室内语义建图中的场所感知方法综述. 自动化学报, 2017, 43(4): 493-508. doi: 10.16383/j.aas.2017.c160350
ZHU Bo, GAO Xiang, ZHAO Yan-Nan. Place Perception for Robot Indoor Semantic Mapping: A Survey. ACTA AUTOMATICA SINICA, 2017, 43(4): 493-508. doi: 10.16383/j.aas.2017.c160350
Citation: ZHU Bo, GAO Xiang, ZHAO Yan-Nan. Place Perception for Robot Indoor Semantic Mapping: A Survey. ACTA AUTOMATICA SINICA, 2017, 43(4): 493-508. doi: 10.16383/j.aas.2017.c160350

机器人室内语义建图中的场所感知方法综述

doi: 10.16383/j.aas.2017.c160350
基金项目: 

国家自然科学基金 61603195

江苏省自然科学基金 BK20140878

南京邮电大学引进人才科研启动基金资助项目 NY214018

南京邮电大学国家自然科学基金孵化项目 NY215131

详细信息
    作者简介:

    高翔 南京邮电大学自动化学院教授.主要研究方向为机器人传感技术.E-mail:gaoxnj@126.com

    赵燕喃 南京邮电大学自动化学院本科生.E-mail:840898594@qq.com

    通讯作者:

    朱博 南京邮电大学自动化学院讲师.2014年获得东南大学控制理论与控制工程博士学位.主要研究方向为机器人环境感知, 机器人视觉, 语义建图.E-mail:zhuboseu@163.com

Place Perception for Robot Indoor Semantic Mapping: A Survey

Funds: 

National Natural Science Foundation of China 61603195

Natural Science Foundation of Jiangsu Province BK20140878

Introduction of talent research start-up fund of NUPT NY214018

Incubation Project for National Natural Science Foundation Project of Nanjing University of Posts and Telecommunications NY215131

More Information
    Author Bio:

    Professor at the School of Automation, Nanjing University of Posts and Telecommunications. Her main research interest is robot sensing technology

    Bachelor student at the School of Automation, Nanjing University of Posts and Telecommunications

    Corresponding author: ZHU Bo Lecturer at the School of Automation, Nanjing University of Posts and Telecommunications. He received his Ph. D. degree from Southeast University in 2014. His research interest covers robot environment perception, robot vision, and semantic mapping. Corresponding author of this paper
  • 摘要: 场所感知问题是机器人语义地图研究的关键问题之一,本文对室内语义地图相关的场所感知方法进行全面综述.首先,根据近年的文献给出场所概念的描述性定义,对研究中涉及的相近术语和概念进行辨析,澄清研究对象和研究主题.然后,根据实现场所感知目标所采用的线索对已有方法进行分类介绍.主要分成3个大类:基于环境布局几何信息的方法、基于环境布局视觉信息的方法、基于用户指导信息的方法,其中各类又根据所用信息特点细分为若干子类.除此之外,将一些特殊研究方法单独归类进行补充说明.阐述各类别方法对场所感知问题的解决思路和工作原理,并指出各种方法特点和局限性.最后,分析了该领域存在的主要问题,并对未来研究方向进行了讨论和展望.
    1)  本文责任编委 徐昕
  • 图  1  场所感知方法分类

    Fig.  1  The category of place perception methods

    图  2  位于房间、门口、走廊时距离传感器数据实例[17]

    Fig.  2  The data instance of range sensors in room, doorway, and corridor[17]

    图  3  3D空间特征向量构成基础[32]

    Fig.  3  The construction base of 3D space feature vector[32]

    图  4  厨房全景图像 (上图为深度图, 下图为反射图)[51]

    Fig.  4  The panoramic images of a kitchen (depth image above and reflectance image below)[51]

    图  5  检测出特征点的3D图像[54]

    Fig.  5  The 3D image including the detected feature points[54]

    图  6  基于NBC的场所感知效果[73]

    Fig.  6  The place perception effect based on NBC[73]

    图  7  人机交互获取环境知识[85]

    Fig.  7  Surrounding knowledge obtaining based on human-robot interaction[85]

    图  8  根据运动传感器推理家具类型[88]

    Fig.  8  Furniture type inferring based on motion sensors[88]

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  • 收稿日期:  2016-04-19
  • 录用日期:  2016-11-08
  • 刊出日期:  2017-04-20

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