@inproceedings{f081f3c7283040bd9c6c757bfde30660,
title = "Development of safety diagnostic robot for industrial plant environment",
abstract = "In this paper, a robot for safety diagnosis is presented to solve the problem of safety diagnosis at industrial plant sites. Safety diagnosis is essential for industrial plants because accidents at industrial plants cause huge economic losses as well as casualties. However, safety diagnosis is difficult due to various dangers such as suffocation and gas explosions in industrial factories. Therefore, we have developed a robot that performs safety diagnoses instead of humans. We designed a mobile robot with various environmental sensors for safety diagnosis and autonomous navigation and installed autonomous mission performance software to enable unmanned safety diagnosis. When a robot receives a mission from the manager, it plans suitable for the mission and moves autonomously through an autonomous navigation algorithm and conducts safety diagnosis at the target point. It also visually shows the current state through the user interface and informs the user of the current diagnostic results. In this paper, we tested robots in an industrial plant environment and confirmed that robots can replace humans.",
keywords = "Autonomous navigation, diagnostic, industrial plants, inspection, robotics, safety diagnostic",
author = "Choi, \{Jun Hyeon\} and An, \{Ye Chan\} and Joo, \{Sung Hyeon\} and Kuc, \{Tae Yong\}",
note = "Publisher Copyright: {\textcopyright} 2021 ICROS.; 21st International Conference on Control, Automation and Systems, ICCAS 2021 ; Conference date: 12-10-2021 Through 15-10-2021",
year = "2021",
doi = "10.23919/ICCAS52745.2021.9650041",
language = "English",
series = "International Conference on Control, Automation and Systems",
publisher = "IEEE Computer Society",
pages = "947--950",
booktitle = "2021 21st International Conference on Control, Automation and Systems, ICCAS 2021",
}