Sim-to-Real Multirotor Controller Single-shot Learning
<|reference_start|>Sim-to-Real Multirotor Controller Single-shot Learning: This paper demonstrates the sim-to-real capabilities of retrospective cost optimization-based adaptive control for multirotor stabilization and trajectory-tracking problems. First, a continuous-time version of the widely used discrete-time retrospective control adaptive control algorithm is developed. Next, a computationally inexpensive 12-degree-of-freedom model of a multirotor is used to learn the control system in a simulation environment with a single trajectory. Finally, the performance of the learned controller is verified in a complex and realistic multirotor model in simulation and with a physical quadcopter in a waypoint command and a helical trajectory command.<|reference_end|>
@article{mirtaba2024sim-to-real,
    title={Sim-to-Real Multirotor Controller Single-shot Learning},
    author={Mohammad Mirtaba, Parham Oveissi, Ankit Goel},
    journal={arXiv preprint arXiv:2410.03815},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.03815},
    primaryClass={eess.SY cs.SY}
}