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...
Main Authors: | , , , |
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Other Authors: | , , |
Format: | Article |
Language: | English |
Published: |
Institute of Electrical and Electronics Engineers (IEEE),
2017-04-05T20:03:20Z.
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Subjects: | |
Online Access: | Get fulltext |