A Novel Technique For Indoor Object Distance Measurement By Using 3D Point Cloud and LiDAR

被引：0
|
作者：
Kim, Jisoo [1 ]
Lee, Dongik [1 ]
机构：
[1] Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea
来源：
2022 22ND INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS 2022) | 2022年
基金：
新加坡国家研究基金会;
关键词：
region-based segmentation; 3D point cloud; indoor mobile robot; LiDAR; ROS; REGION-BASED SEGMENTATION;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The SLAM (Simultaneous Localization and Mapping) technology has been widely exploited to collect information of location and environment for indoor mobile robots. Usually, SLAM has a single LiDAR(Light Detection and Ranging) sensor which reveals its vulnerability to complex terrain or distinction between objects. A possible solution to overcome this problem is the data fusion technique with LiDAR and depth cameras. This paper presents a novel data fusion technique with LiDAR data and 3D-point cloud data for estimating the surrounding object locations. In the proposed technique, the surrounding object location data are extracted using the region-based segmentation technique in real time using 3D-point cloud images. The effectiveness of the proposed algorithm is demonstrated with a set of experiments based on ROS (Robot Operating System).
引用
收藏
页码：1044 / 1048
页数：5
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