@inproceedings{cd31763eb3ee406385edeb62d1c02fcd,
title = "A Novel Technique For Indoor Object Distance Measurement By Using 3D Point Cloud and LiDAR",
abstract = "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).",
keywords = "3D point cloud, indoor mobile robot, LiDAR, region-based segmentation, ROS",
author = "Jisoo Kim and Dongik Lee",
note = "Publisher Copyright: {\textcopyright} 2022 ICROS.; 22nd International Conference on Control, Automation and Systems, ICCAS 2022 ; Conference date: 27-11-2022 Through 01-12-2022",
year = "2022",
doi = "10.23919/ICCAS55662.2022.10003884",
language = "English",
series = "International Conference on Control, Automation and Systems",
publisher = "IEEE Computer Society",
pages = "1044--1048",
booktitle = "2022 22nd International Conference on Control, Automation and Systems, ICCAS 2022",
address = "United States",
}