Learning Ability Models for Human-Robot Collaboration - Archive ouverte HAL Access content directly
Conference Papers Year :

Learning Ability Models for Human-Robot Collaboration


Our vision is a pro-active robot that assists elderly or disabled people in everyday activities. Such a robot needs knowledge in the form of prediction models about a person’s abilities, preferences and expectations in order to decide on the best way to assist. We are interested in learning such models from observation. We report on a first approach to learn ability models for manipulation tasks and identify some general challenges for the acquisition of human models.
Fichier principal
Vignette du fichier
kirsch10learning.pdf (86.61 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01405755 , version 1 (30-11-2016)


  • HAL Id : hal-01405755 , version 1


Alexandra Kirsch, Fan Cheng. Learning Ability Models for Human-Robot Collaboration. Robotics: Science and Systems (RSS) --- Workshop on Learning for Human-Robot Interaction Modeling, 2010, Zaragoza, Spain. ⟨hal-01405755⟩
30 View
15 Download


Gmail Facebook Twitter LinkedIn More