Efficient Model Learning from Joint-Action Demonstrations for Human-Robot Collaborative Tasks

We present a framework for automatically learning human user models from joint-action demonstrations that enables a robot to compute a robust policy for a collaborative task with a human. First, the demonstrated action sequences are clustered into different human types using an unsupervised learning...

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Vydané v:	Hri '15: ACM/IEEE International Conference on Human-Robot Interaction USB Stick s. 189 - 196
Hlavní autori:	Nikolaidis, Stefanos, Ramakrishnan, Ramya, Keren Gu, Shah, Julie
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	ACM 02.03.2015
Predmet:	Clustering algorithms Collaboration Computational modeling Data models Markov processes Robots Task analysis
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