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, Jinseok; Lee, Keon-Pyo; Choi, Euteum; Jun, Yong-Kee; Lee, 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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Collections - 공과대학 > Department of Aerospace and Software Engineering > Journal Articles
- 공학계열 > 항공우주소프트웨어공학과 > Journal Articles
- 공학계열 > AI융합공학과 > Journal Articles

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