Temporal Alignment and Demonstration Selection as Pre-Processing Phase for Learning by Demonstration
International audience Robots can benefit from users’ demonstrations to learnmotions. To be efficient, a pre-processing phase needsto be performed on data recorded from demonstrations.This paper presents pre-processing methods developedfor Learning By Demonstration (LbD). Thepre-processing phase con...
Published in: | The International FLAIRS Conference Proceedings |
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Main Authors: | , , , |
Other Authors: | , , , , , , , , |
Format: | Conference Object |
Language: | English |
Published: |
HAL CCSD
2022
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Subjects: | |
Online Access: | https://hal.science/hal-03670974 https://doi.org/10.32473/flairs.v35i.130649 |
Summary: | International audience Robots can benefit from users’ demonstrations to learnmotions. To be efficient, a pre-processing phase needsto be performed on data recorded from demonstrations.This paper presents pre-processing methods developedfor Learning By Demonstration (LbD). Thepre-processing phase consists in methods composedof alignment algorithms and algorithms that select thegood demonstrations. In this paper we propose sixmethods and compare them to select the best one. |
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