Building a grid-semantic map for the navigation of service robots through human-robot interaction
Building a grid-semantic map for the navigation of service robots through human-robot interaction
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通过人机交互构建服务机器人导航的网格语义图
DOI：
10.1016/j.dcan.2015.09.002
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
W. Pan
中科院分区：
文献类型：
--
作者：
Cheng Zhao;Weixing Mei;W. Pan
本文提出了一种构建网格语义地图的交互式方法，用于室内环境中服务机器人的导航。它基于机器人操作系统（ROS）框架，包含交互模块、控制模块、导航模块和建图模块四个模块。在其开发过程中，重点关注了三个具有挑战性的问题：（i）如何在测绘和导航过程中有效地部署人类语音和机器人视觉信息； (ii) 语义名称如何与在线网格语义地图中的坐标数据相结合； (iii)如何在基于修改后的粒子群最大粒子权重的全局定位中使用定位-评估-重定位方法。在走廊、办公室等模拟环境和真实环境中进行了大量实验，验证其可行性和性能。
This paper presents an interactive approach to the construction of a grid-semantic map for the navigation of service robots in an indoor environment. It is based on the Robot Operating System (ROS) framework and contains four modules, namely Interactive Module, Control Module, Navigation Module and Mapping Module. Three challenging issues have been focused during its development: (i) how human voice and robot visual information could be effectively deployed in the mapping and navigation process; (ii) how semantic names could combine with coordinate data in an online Grid-Semantic map; and (iii) how a localization–evaluate–relocalization method could be used in global localization based on modified maximum particle weight of the particle swarm. A number of experiments are carried out in both simulated and real environments such as corridors and offices to verify its feasibility and performance.