Novel Mobile Robot Concept for Human Detection in Fire Smoke Indoor Environments using Deep Learning
ORCID
https://orcid.org/0000-0002-4237-6327
Document Type
Article
Disciplines
Electrical and Computer Engineering | Engineering | Mechanical Engineering
Abstract
Human victim detection in smoky indoor environments during search and rescue missions is still challenging. This situation is due to the fact that fire fighters are on the one hand exposed to thermal radiation and unstable building structures. On the other hand, their cognitive fatigue, due to long search and rescue missions, reduce the efficient victim detection in such hazardous environments with limited visibility. In this paper, a novel concept of a remote-controlled and heat protected unmanned ground vehicle with victim detection system is presented, which detects missing victims in real time in smoky indoor environments and display its localization with detection rate to an operator outside the danger zone. The victim detection system, based on a trained deep learning model, is designed to address the specific properties of victims, which are for instance characterised by a lying position. The novel concept provides a framework for the design and the validation of the mobile robot with the victim detection system.
Recommended Citation
Sebastian Gelfert. 2022. Novel Mobile Robot Concept for Human Detection in Fire Smoke Indoor Environments using Deep Learning. In 2022 8th International Conference on Robotics and Artificial Intelligence (ICRAI 2022), November 18–20, 2022, Singapore, Singapore. ACM, New York, NY, USA, 7 pages. https://doi.org/10.1145/3573910.3573913
Publication Details
Proceedings of the 8th International Conference on Robotics and Artificial Intelligence, Singapore, Singapore, ICRAI '22. © 2022 Association for Computing Machinery.