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Computer Science > Robotics

arXiv:2108.13803 (cs)
[Submitted on 31 Aug 2021 (v1), last revised 14 Jan 2022 (this version, v4)]

Title:Manipulation of Camera Sensor Data via Fault Injection for Anomaly Detection Studies in Verification and Validation Activities For AI

Authors:Alim Kerem Erdogmus, Mustafa Karaca, Assist. Ugur Yayan
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Abstract:In this study, the creation of a database consisting of images obtained as a result of deformation in the images recorded by these cameras by injecting faults into the robot camera nodes and alternative uses of this database are explained. The study is based on an existing camera fault injection software that injects faults into the cameras of a working robot and collects the normal and faulty images recorded during this injection. The database obtained in the study is a source for the detection of anomalies that may occur in robotic systems. Within the scope of this study, a database of 10000 images consisting of 5000 normal and 5000 faulty images was created. Faulty images were obtained by injecting seven different types of image faults, namely erosion, dilation, opening, closing, gradient, motionblur and partialloss, at different times while the robot was operating.
Comments: 7 pages, 9 figures, Provided by Inovasyon Muhendislik
Subjects: Robotics (cs.RO)
ACM classes: H.2.4; I.4.3; B.4.5
Cite as: arXiv:2108.13803 [cs.RO]
  (or arXiv:2108.13803v4 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2108.13803

Submission history

From: Alim Kerem Erdogmus [view email]
[v1] Tue, 31 Aug 2021 12:47:03 UTC (1,162 KB)
[v2] Fri, 1 Oct 2021 14:31:55 UTC (1,151 KB)
[v3] Tue, 5 Oct 2021 11:50:36 UTC (1,808 KB)
[v4] Fri, 14 Jan 2022 11:33:01 UTC (568 KB)
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