Publication: A Benchmark Comparison of Learned Control Policies for Agile Quadrotor Flight
A Benchmark Comparison of Learned Control Policies for Agile Quadrotor Flight
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Kaufmann, E., Bauersfeld, L., & Scaramuzza, D. (2022). A Benchmark Comparison of Learned Control Policies for Agile Quadrotor Flight. Proceedings of the IEEE International Conference on Robotics and Automation, 10504–10510. https://doi.org/10.1109/ICRA46639.2022.9811564
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Quadrotors are highly nonlinear dynamical systems that require carefully tuned controllers to be pushed to their physical limits. Recently, learning-based control policies have been proposed for quadrotors, as they would potentially allow learning direct mappings from high-dimensional raw sensory observations to actions. Due to sample inefficiency, training such learned controllers on the real platform is impractical or even impossible. Training in simulation is attractive but requires to transfer policies between domains, which deman
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- Bauersfeld, Leonard
- Scaramuzza, Davide
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Kaufmann, E., Bauersfeld, L., & Scaramuzza, D. (2022). A Benchmark Comparison of Learned Control Policies for Agile Quadrotor Flight. Proceedings of the IEEE International Conference on Robotics and Automation, 10504–10510. https://doi.org/10.1109/ICRA46639.2022.9811564
