DEVELOPMENT OF A FAULT INJECTION TOOL & DATASET FOR VERIFICATION OF CAMERA BASED PERCEPTION IN ROBOTIC SYSTEMS

Autor: Alim Kerem Erdoğmuş, Uğur Yayan
Jazyk: English<br />Turkish
Rok vydání: 2022
Předmět:
Zdroj: Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi, Vol 30, Iss 3, Pp 328-339 (2022)
Druh dokumentu: article
ISSN: 2630-5712
DOI: 10.31796/ogummf.1054761
Popis: Nowadays, camera-based perception is most popular topic in robotic systems. Verification of camera-based perception systems are crucial and difficult with current tools and methods. This study proposes Camera Fault Injection Tool (CamFITool), which enables different kind of fault injection methods to RGB and TOF cameras in order to perform verification and validation activities on robotic systems. Besides, Fault Injected Image Database which is created by CamFITool is introduced. In addition, the study guides to readers to create new datasets by injecting faults into existing image libraries or camera streams with CamFITool. As a result, CamFITool, an open-source fault injection tool, which is a critical tool for assessing of fault tolerant systems’ safety and security, is proposed. Also, a fault injected image dataset created by CamFITool for verification of camera-based perception studies in robotic systems is given.
Databáze: Directory of Open Access Journals