Energy-based regularization on residual dynamics learning improves neural MPC for aerial robots, cutting positional error 23% versus analytical models and boosting stability over unregularized neural MPC in real flights.
Design, control, and motion planning for a root-perching rotor-distributed manipulator
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Energy-based Regularization for Learning Residual Dynamics in Neural MPC for Omnidirectional Aerial Robots
Energy-based regularization on residual dynamics learning improves neural MPC for aerial robots, cutting positional error 23% versus analytical models and boosting stability over unregularized neural MPC in real flights.