Neuroflight: Next Generation Flight Control Firmware
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Abstract (arXiv)
Little innovation has been made to low-level attitude flight control used by uncrewed aerial vehicles (UAVs), which still predominantly uses the classical PID controller. In this work we introduce Neuroflight, the first open source neuro-flight controller firmware. We present our toolchain for training a neural network in simulation and compiling it to run on embedded hardware. Challenges faced jumping from simulation to reality are discussed along with our solutions. Our evaluation shows the neural network can execute at over 2.67kHz on an Arm Cortex-M7 processor and flight tests demonstrate a quadcopter running Neuroflight can achieve stable flight and execute aerobatic maneuvers.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Jan 2019.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 2.
4 papers.
- 2021Data-Efficient Deep Reinforcement Learning for Attitude Control of Fixed-Wing UAVs: Field Experimentscited by 4
- 2021AutoPilot: Automating SoC Design Space Exploration for SWaP Constrained Autonomous UAVscited by 0
- 2023Sim-Anchored Learning for On-the-Fly Adaptationcited by 0
- 2023Execution time budget assignment for mixed criticality systemscited by 0
- 2023Execution time budget assignment for mixed criticality systems14 Nov 2023
- 2023Sim-Anchored Learning for On-the-Fly Adaptation17 Jan 2023
- 2021Data-Efficient Deep Reinforcement Learning for Attitude Control of Fixed-Wing UAVs: Field Experiments7 Nov 2021
- 2021AutoPilot: Automating SoC Design Space Exploration for SWaP Constrained Autonomous UAVs5 Feb 2021