ISPIL: Interactive Sub-Goal-Planning Imitation Learning for Long-Horizon Tasks With Diverse Goals

Imitation Learning (IL) is a promising approach for teaching tasks to robots by human demonstrations, although it faces challenges from long-horizon tasks and diverse goals in real-world settings. These issues stem from (i) a distribution mismatch between demonstrations and real-world execution and...

Descrizione completa

Dettagli Bibliografici

Autori principali:	Cynthia Ochoa, Hanbit Oh, Yuhwan Kwon, Yukiyasu Domae, Takamitsu Matsubara
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	IEEE 2024-01-01
Serie:	IEEE Access
Soggetti:	Interactive imitation learning learning-to-plan hierarchical policy
Accesso online:	https://ieeexplore.ieee.org/document/10811934/
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!