ICRA 2022Poster

Watch and Learn: Learning to control feedback linearizable systems from expert demonstrations

Authors: Alimzhan Sultangazin, Luigi Pannocchi, Lucas Fraile, Paulo Tabuada

Abstract

In this paper, we revisit the problem of learning a stabilizing controller from a finite number of demonstrations by an expert. By focusing on feedback linearizable systems, we show how to combine expert demonstrations into a stabilizing controller, provided that demonstrations are sufficiently long and there are at least n+1n+1 of them, where nn is the number of states of the system being controlled. The results are experimentally demonstrated on a CrazyFlie 2.0 quadrotor.

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