On Choosing Structure for a Machine Learning-based Reaction Force Predictor for Walking Robots

This paper focuses on the topic of contact reaction prediction for walking robots, namely on the analysis of performances on different structures of the machine-learning-based predictors. Predicting reaction forces is important due to the fact that it can allow us to retrieve a simplified model of t...

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Bibliographic Details
Published in:Journal of physics. Conference series 2021-03, Vol.1831 (1), p.12018
Main Authors: Zalyaev, E, Savin, S, Salikhzyanov, A, Golousov, S
Format: Article
Language:English
Subjects:
Data collection
Data compression
Feature extraction
Machine learning
Physics
Robots
Walking
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Summary:This paper focuses on the topic of contact reaction prediction for walking robots, namely on the analysis of performances on different structures of the machine-learning-based predictors. Predicting reaction forces is important due to the fact that it can allow us to retrieve a simplified model of the contact scenario, as was proposed in the literature preciously. This allows to turn the problem of contact model identification into a data collection and processing problem. In order to do it effectively, both a data compression (feature extraction) and regression strategies might be used. This research provides an analysis of both with respect to the discussed problem.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1831/1/012018