Drone failures don’t have to end in loss.
Turning Failures into Controlled Outcomes.
Adaptive Resilient UAV System (ARUS) is a supervised-autonomy framework designed to enable industrial drones to detect, respond to, and survive real-time system degradation or failure while maintaining mission continuity.
Current UAV operations rely heavily on predefined fail-safes such as Return-To-Launch or immediate landing. These binary responses fail to account for real-world mission complexity, dynamic environments, and partial system failures. ARUS introduces an intelligence layer that transforms UAV behavior from reactive to adaptive.
The system integrates with existing autopilot platforms such as ArduPilot through a companion computer, enabling continuous telemetry analysis and intelligent decision-making without modifying core flight stability systems.
ARUS continuously monitors key flight parameters including attitude stability, vibration signatures, energy consumption, navigation integrity, and control effort. These inputs are processed through a multi-signal health scoring model capable of identifying anomalies such as propulsion imbalance, battery degradation, or sensor inconsistency.
When abnormal conditions are detected, ARUS classifies severity and initiates a structured response. Instead of defaulting to mission termination, the system dynamically adapts the mission profile. This includes reducing speed, simplifying route complexity, skipping non-critical objectives, or transitioning to safer flight modes.
A core feature of ARUS is operator-in-the-loop supervisory control. The system provides real-time alerts and recommended actions while preserving human authority. Operators can accept, modify, or override system decisions, ensuring regulatory compatibility and operational trust.
A representative use case includes detection of propulsion asymmetry during flight. ARUS identifies instability through combined indicators such as yaw drift, increased control effort, and vibration anomalies. It then stabilizes the aircraft and recommends a controlled landing or return-to-launch based on mission context.
The system is designed for high-risk industrial applications including infrastructure inspection, public safety operations, and heavy-lift missions, where failure survival and mission continuity are critical.
Like this entry?
-
About the Entrant
- Name:Ismar Avdic
- Type of entry:individual
- Software used for this entry:ArduPilot, MavLink, Python,
- Patent status:none



