Temporal Alignment and Demonstration Selection as Pre-Processing Phase for Learning by Demonstration - Jérémie Donjat; Amélie Legeleux; Cédric Buche; Dominique Duhaut (Proceedings of the International Florida Artificial Intelligence Research Society Conference)
Robots can benefit from users’ demonstrations to learn motions. To be efficient, a pre-processing phase needs to be performed on data recorded from demonstrations. This paper presents pre-processing methods developed for Learning By Demonstration (LbD). The pre-processing phase consists in methods composed of alignment algorithms and algorithms that select the good demonstrations. In this paper we propose six methods and compare them to select the best one.