From control model to program: Investigating robotic aerial vehicle accidents with MAYDAY

Taegyu Kim, Chung Hwan Kim, Altay Ozen, Fan Fei, Zhan Tu, Xiangyu Zhang, Xinyan Deng, Dave Tian, Dongyan Xu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations


With wide adoption of robotic aerial vehicles (RAVs), their accidents increasingly occur, calling for in-depth investigation of such accidents. Unfortunately, an inquiry to “why did my drone crash” often ends up with nowhere, if the root cause lies in the RAV's control program, due to the key challenges in evidence and methodology: (1) Current RAVs' flight log only records high-level vehicle control states and events, without recording control program execution; (2) The capability of “connecting the dots” - from controller anomaly to program variable corruption to program bug location - is lacking. To address these challenges, we develop MAYDAY, a cross-domain post-accident investigation framework by mapping control model to control program, enabling (1) in-flight logging of control program execution, and (2) traceback to the control-semantic bug that led to an accident, based on control- and program-level logs. We have applied MAYDAY to ArduPilot, a popular open-source RAV control program that runs on a wide range of commodity RAVs. Our investigation of 10 RAV accidents caused by real ArduPilot bugs demonstrates that MAYDAY is able to pinpoint the root causes of these accidents within the program with high accuracy and minimum runtime and storage overhead. We also found 4 recently patched bugs still vulnerable and alerted the ArduPilot team.

Original languageEnglish (US)
Title of host publicationProceedings of the 29th USENIX Security Symposium
PublisherUSENIX Association
Number of pages18
ISBN (Electronic)9781939133175
StatePublished - 2020
Event29th USENIX Security Symposium - Virtual, Online
Duration: Aug 12 2020Aug 14 2020

Publication series

NameProceedings of the 29th USENIX Security Symposium


Conference29th USENIX Security Symposium
CityVirtual, Online

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems
  • Safety, Risk, Reliability and Quality


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