flight control software
RisConFix: LLM-based Automated Repair of Risk-Prone Drone Configurations
Han, Liping, Nie, Tingting, Yu, Le, Hu, Mingzhe, Yue, Tao
Flight control software is typically designed with numerous configurable parameters governing multiple functionalities, enabling flexible adaptation to mission diversity and environmental uncertainty. Although developers and manufacturers usually provide recommendations for these parameters to ensure safe and stable operations, certain combinations of parameters with recommended values may still lead to unstable flight behaviors, thereby degrading the drone's robustness. To this end, we propose a Large Language Model (LLM) based approach for real-time repair of risk-prone configurations (named RisConFix) that degrade drone robustness. RisConFix continuously monitors the drone's operational state and automatically triggers a repair mechanism once abnormal flight behaviors are detected. The repair mechanism leverages an LLM to analyze relationships between configuration parameters and flight states, and then generates corrective parameter updates to restore flight stability. To ensure the validity of the updated configuration, RisConFix operates as an iterative process; it continuously monitors the drone's flight state and, if an anomaly persists after applying an update, automatically triggers the next repair cycle. We evaluated RisConFix through a case study of ArduPilot (with 1,421 groups of misconfigurations). Experimental results show that RisConFix achieved a best repair success rate of 97% and an optimal average number of repairs of 1.17, demonstrating its capability to effectively and efficiently repair risk-prone configurations in real time.
- Information Technology (0.93)
- Transportation > Air (0.47)
- Information Technology > Artificial Intelligence > Natural Language > Large Language Model (1.00)
- Information Technology > Artificial Intelligence > Robots > Autonomous Vehicles > Drones (0.69)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.48)
Airbus to Use AI in Designing FCAS Flight Control Software - Avionics
At the 2019 Paris Air Show, Dassault Aviation showed a mockup of the FCAS sixth generation fighter jet for the first time publicly. A new partnership between ANSYS and Airbus Defense and Space will develop a new artificial intelligence design tool to create the embedded flight control software for Europe's Future Combat Air System (FCAS). FCAS is a next-generation air combat development program involving France, Germany and now Spain to develop a system of fully automated remote air platforms and sixth-generation fighters that will replace the current generation of Eurofighter and Rafale jets operated by those three countries. Dassault and Airbus are the lead prime manufacturers for the FCAS program. A mockup of the future FCAS stealth fighter concept was shown publicly for the first time during the 2019 Paris Air Show.
- Aerospace & Defense > Aircraft (1.00)
- Government > Military > Air Force (0.63)