01 · AFC
Autonomous flight control
Learning-based and model-informed control systems for aerial platforms operating under uncertainty, nonlinear dynamics, and mission-level constraints.
DOMAIN · CONTROL SYSTEMSSCOPE · UAV / HYBRID
Autonomous intelligence
for aerial systems.
XONI develops adaptive autonomy for aerial systems at the intersection of flight dynamics, control theory, high-fidelity simulation, and machine intelligence.
Building simulation-driven autonomy toward deployable aerial systems for cooperative formations and complex missions.
§ 01— Direction
Where flight dynamics, control, and learning converge.
XONI develops autonomy at the intersection of aerospace engineering, control theory, high-fidelity simulation, and machine intelligence — building toward adaptive aerial platforms for complex real-world missions.
§ 02— Focus areas
Built across flight control, simulation, and coordination.
XONI builds the technical core of aerial autonomy across three engineering tracks — flight control, simulation, and cooperative systems.
02 · SIM
High-fidelity simulation
Simulation environments, digital twins, and dynamics models designed to reduce the gap between offline training and real-world flight behavior.
DOMAIN · DIGITAL TWINSSCOPE · 6-DoF / RL
03 · COOP
Cooperative aerial systems
Formation control, multi-agent coordination, and autonomy architectures for distributed aerial missions.
DOMAIN · MULTI-AGENTSCOPE · FORMATIONS
§ 03— Technical foundation
Technical foundation.
XONI’s technical foundation rests on applied aerospace autonomy research in reinforcement-learning flight control, high-fidelity UAV simulation, and guidance, navigation & control for complex aerial platforms.
Reinforcement-learning flight controlHigh-fidelity UAV simulationGuidance, navigation & controlMulti-agent coordination
§ 04— Founder-led engineering
Founder-led engineering.
XONI is led by Nikolay Lyan, an aerospace engineer building simulation-driven autonomy for real-world aerial systems.
His research and hands-on engineering bridge reinforcement learning, high-fidelity digital twins, and GNC to develop adaptive autonomous platforms capable of operating under uncertainty and dynamic conditions.
- First-author AIAA SciTech publications on RL-based flight control and hybrid airship simulation
- Developed high-fidelity 6-DoF digital twins for autonomous UAV research
- Built PPO-based autopilot policies for waypoint tracking in unseen missions
- IMechE UAS Challenge 2018 — Overall Grand Champion team member
- Practical UAV prototyping exposure: composite fabrication workflows, Li-ion battery pack assembly, power integration, and experimental test setups
§ 05— Next milestones
Next milestones.
XONI is advancing its technical foundation through simulation environments, autonomy experiments, formation-control studies, and early platform development.
- M-01Publish technical notes and simulation breakdowns
- M-02Release formation-control and autonomy experiments
- M-03Develop early aerial platform concepts
- M-04Expand toward experimental validation and hardware integration
- M-05Prepare selected technical collaboration tracks
§ 06— Development status
Development status.
XONI is building and validating its core autonomy stack — from high-fidelity simulation to flight-control architectures and early platform concepts — progressing toward real-world experimental demonstrations.
— Contact
Technical contact.
For technical discussions, research alignment, or selected early collaboration.
contact@xoni.ai