Learning Control

Sylvain Calinon, Dongheui Lee

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

35 Scopus citations

Abstract

This chapter presents an overview of learning approaches for the acquisition of controllers and movement skills in humanoid robots. The term learning control refers to the process of acquiring a control strategy to achieve a task. While the definition is in some cases restrained to trial-and-error learning, we present here learning control in a broader perspective, with a focus on the representation of skills to be acquired, and on the different learning strategies that can contribute to the acquisition of robust and adaptive controllers for humanoids.

Original languageEnglish
Title of host publicationHumanoid Robotics
Subtitle of host publicationA Reference
PublisherSpringer Netherlands
Pages1261-1312
Number of pages52
ISBN (Electronic)9789400760462
ISBN (Print)9789400760455
DOIs
StatePublished - 1 Jan 2018
Externally publishedYes

Keywords

  • Dynamic Movement Primitives (DMP)
  • Gaussian Mixture Regression (GMR)
  • Hidden semi-Markov Model (HSMM)
  • Humanoid Robotics
  • Kinesthetic Teaching

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