Work

Anomaly Detection in Robotic Aerospace Drilling using Data Driven Methods*

Year: 2025

Type: conference-paper

Source: 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)

DOI: 10.1109/case58245.2025.11164033

Authors: B. Pamplin, P. Edwards, G. Martínez-Arellano, S. Piano, S. Ratchev

Institutions: University of Nottingham, Airbus (United Kingdom)

Language: English

Topic: Anomaly Detection Techniques and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W4414432308

FWCI: 1.006

Cites: 20

Cited by: 1

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