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Learning-from-Observation

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Computer Vision

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Synonyms

Imitation learning; Learning from demonstration; Programming by demonstration

Related Concepts

Definition

Learning-from-Observation is the framework to generate robot’s (or other agent’s) movement to achieve a target task with less user’s programming effort. In this framework, a user just demonstrates the target task and a robot learns the method to reproduce the target task from the observation.

Background

One goal in robotics and artificial intelligence (AI) fields is to achieve any target tasks by a robot with less user’s programming efforts. To achieve this purpose, Learning-from-Observation (LFO) framework attracts an attention. In this framework, a user just demonstrates the target task and a robot learns the method to reproduce the target task from the observation. The user is not required to have special skills on robotics. Note that an agent that the user teaches is not limited to a robot.

In a scientific point of view, it is...

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Author information

Authors and Affiliations

  1. Division of Information Science, Nara Institute of Science and Technology, Nara, Japan

    Jun Takamatsu

Authors
  1. Jun Takamatsu
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Corresponding author

Correspondence to Jun Takamatsu .

Section Editor information

  1. Microsoft Research, microsoft, Redmond, USA

    Katsushi Ikeuchi

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Takamatsu, J. (2021). Learning-from-Observation. In: Computer Vision. Springer, Cham. https://doi.org/10.1007/978-3-030-03243-2_869-1

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  • DOI: https://doi.org/10.1007/978-3-030-03243-2_869-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03243-2

  • Online ISBN: 978-3-030-03243-2

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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