Robot Task-Constrained Optimization and Adaptation with Probabilistic Movement Primitives

Robot Task-Constrained Optimization and Adaptation with Probabilistic Movement Primitives

Enabling a robot to learn skills from a human and adapt to different task scenarios will enable the use of robots in manufacturing to improve efficiency. Movement Primitives (MPs) are prominent tools for encoding skills. This paper investigates how to learn MPs from a small number of human demonstra...

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Bibliographic Details
Main Authors: Guanwen Ding, Xizhe Zang, Xuehe Zhang, Changle Li, Yanhe Zhu, Jie Zhao
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Biomimetics
Subjects:
human–robot skill transfer
learning from demonstration
probabilistic movement primitives
task-constrained optimization
movement adaptation
Online Access:https://www.mdpi.com/2313-7673/9/12/738
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