Learning Ability Models for Human-Robot Collaboration

Abstract : 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.
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Communication dans un congrès
Robotics: Science and Systems (RSS) --- Workshop on Learning for Human-Robot Interaction Modeling, 2010, Zaragoza, Spain
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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〉

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