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Reinforcement learning helps quadrotors track trajectories despite disturbances

Original: In our SPIE paper "Enhancing quadrotor trajectory tracking under disturbances and degraded sensing: a reinforcement lear

Researchers at the Royal Military Academy in Belgium have published a SPIE paper presenting a reinforcement learning framework that improves quadrotor trajectory tracking when drones face disturbances and degraded sensing. The work targets robust control for agile drone flight, and the team has released its models and implementation publicly so others can explore and build on the approach.

Why now: The researchers are promoting their newly published paper and open-sourced models to the robotics community.

SPIERoyal Military Academyquadrotor dronesreinforcement learning

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Evidence

• In our SPIE paper "Enhancing quadrotor trajectory tracking under disturbances and degraded sensing: a reinforcement learning framework" we develop robust control strategies for agile drone flights. We've made our models and implementation available so you can explore the… · ras@social.rma.ac.be · 3

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