Comparing Skill Transfer Between Full Demonstrations and Segmented Sub-Tasks for Neural Dynamic Motion Primitives

Comparing Skill Transfer Between Full Demonstrations and Segmented Sub-Tasks for Neural Dynamic Motion Primitives

Programming by demonstration has shown potential in reducing the technical barriers to teaching complex skills to robots. Dynamic motion primitives (DMPs) are an efficient method of learning trajectories from individual demonstrations using second-order dynamic equations. They can be expanded using...

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Bibliographic Details
Main Authors: Geoffrey Hanks, Gentiane Venture, Yue Hu
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Machines
Subjects:
learning from demonstrations
robot manipulator
machine learning
neural dynamic motion primitives
Online Access:https://www.mdpi.com/2075-1702/12/12/872
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