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무인항공기 시스템의 건전성 관리를 위한 소프트웨어 수행 오류 진단Software Execution Error Diagnosis for UAS Health Management

Other Titles
Software Execution Error Diagnosis for UAS Health Management
Authors
Park, JinseokLee, Keon-PyoChoi, EuteumJun, Yong-KeeLee, Seongjin
Issue Date
Apr-2025
Publisher
한국항공우주학회
Keywords
Health Management; On-the-Fly Diagnosis; Software Error; UAS
Citation
한국항공우주학회지, v.53, no.4, pp 433 - 444
Pages
12
Indexed
SCOPUS
ESCI
KCI
Journal Title
한국항공우주학회지
Volume
53
Number
4
Start Page
433
End Page
444
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/77919
DOI
10.5139/JKSAS.2025.53.4.433
ISSN
1225-1348
2287-6871
Abstract
Health management of Unmanned Aerial Systems (UAS) ensures safe and reliable operation by detecting, diagnosing, predicting, and mitigating errors that occur during operation. Software errors in UAS are one of the significant causes of system failures, making health management necessary. However, existing research on UAS health management primarily addresses software errors caused by hardware and data, failing to diagnose internal execution errors within the software. This study introduces Software Health Diagnosis Sensor (SHDS) that diagnoses internal software execution errors in real-time within UAS. SHDS monitors thread access events to shared variables in real-time to diagnose concurrency errors, a type of software execution error. Experiments were conducted on 13 cases in the ArduPilot Software-In-The-Loop (SITL) environment to demonstrate SHDS's capability in diagnosing concurrency errors and the feasibility of asymmetric race repair. The experimental results show that SHDS accurately diagnoses all 13 concurrency errors with an average overhead of approximately 3.40% and successfully repairs eight asymmetric races with an average overhead of approximately 5.39%. © 2025 The Korean Society for Aeronautical and Space Sciences.
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공과대학 > Department of Aerospace and Software Engineering > Journal Articles
공학계열 > 항공우주소프트웨어공학과 > Journal Articles
공학계열 > AI융합공학과 > Journal Articles

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IT공과대학 (소프트웨어공학과)
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