Local Koopman Operators for Data-Driven Control of Robotic Systems

@article{Mamakoukas2019LocalKO,
  title={Local Koopman Operators for Data-Driven Control of Robotic Systems},
  author={Giorgos Mamakoukas and Maria L. Casta{\~n}o and Xiaobo Tan and Todd D. Murphey},
  journal={Robotics: Science and Systems XV},
  year={2019}
}
This paper presents a data-driven methodology for linear embedding of nonlinear systems. [] Key Method With the linear representation, the nonlinear system is then controlled with an LQR feedback policy, the gains of which need to be calculated only once. As a result, the approach enables fast control synthesis. We demonstrate the efficacy of the approach with simulations and experimental results on the modeling and control of a tail-actuated robotic fish and show that the proposed policy is comparable to…

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