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

被引：2
|
作者：
Sultangazin, Alimzhan [1 ]
Pannocchi, Luigi [1 ]
Fraile, Lucas [1 ]
Tabuada, Paulo [1 ]
机构：
[1] Univ Calif Los Angeles, Dept Elect & Comp Engn, Los Angeles, CA 90024 USA
来源：
2022 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, ICRA 2022 | 2022年
关键词：
D O I：
10.1109/ICRA46639.2022.9812054
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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 + 1 of them, where n is the number of states of the system being controlled. The results are experimentally demonstrated on a CrazyFlie 2.0 quadrotor.
引用
收藏
页码：8577 / 8583
页数：7
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