Development and control of a modular snake-like robot with a biomimetic approach for post-disaster search and condition monitoring
2024
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Advisor: Prof. Dr. Sezai Taşkın
Abstract (EN)
The limited use of technological equipment in preliminary detection efforts during natural disasters leads to an increased reliance on human labor. This dependency also introduces human emotions into disaster management processes. While this can be beneficial in some scenarios, it may also inevitably endanger the lives of individuals trapped in accessible or inaccessible locations within the disaster area. The inadequate utilization of portable and remotely controlled technological equipment in high-risk zones for preliminary detection also puts search and rescue teams at risk. Moreover, the unpredictable and asymmetrical conditions of debris in disaster zones often challenge the technical capabilities of search and rescue teams, imposing limitations on the use of conventional technological equipment. This thesis aims to develop a bionic snake robot designed to conduct preliminary detection operations in disaster areas by maneuvering through small gaps in the debris or in standing portions of collapsed structures. The robot is intended to utilize thermal imaging and analysis techniques to relay the location and condition of disaster victims to the search and rescue team via a user interface. The bionic snake robot, designed with consideration of challenging environmental conditions, features a mechanically robust structure and is controlled via industrial computer software. The kinematic structure of the robot, designed with eight degrees of freedom, enables both crawling and lateral movement. In the fuzzy logic control algorithm, the state of the debris is categorized as undamaged, slightly damaged, moderately damaged, severely damaged, or collapsed.
Author
Gökhan Çetin
Institution
How to Cite
Gökhan Çetin (Master Thesis). Development and control of a modular snake-like robot with a biomimetic approach for post-disaster search and condition monitoring, 2024, Manisa Celal Bayar University.
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