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...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Guanwen Ding, Xizhe Zang, Xuehe Zhang, Changle Li, Yanhe Zhu, Jie Zhao
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	MDPI AG 2024-12-01
Sarja:	Biomimetics
Aiheet:	human–robot skill transfer learning from demonstration probabilistic movement primitives task-constrained optimization movement adaptation
Linkit:	https://www.mdpi.com/2313-7673/9/12/738
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