Neuroflight: Next Generation Flight Control Firmware
William Koch, Renato Mancuso, Azer Bestavros

TL;DR
Neuroflight introduces an open source neural network-based flight controller for UAVs, demonstrating stable flight and aerobatic capabilities on embedded hardware, surpassing traditional PID controllers.
Contribution
It is the first open source neuro-flight controller firmware with a complete toolchain for training and deployment on embedded systems.
Findings
Neural network runs at over 2.67kHz on Cortex-M7
Quadcopter achieves stable flight and aerobatic maneuvers
Addresses simulation-to-reality transfer challenges
Abstract
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.
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Taxonomy
TopicsRobotic Path Planning Algorithms · Autonomous Vehicle Technology and Safety · Adaptive Control of Nonlinear Systems
