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Skill Generalization via Inference-Based Planning

posted Jul 4, 2017, 4:35 PM by Reza Ahmadzadeh
Muhammad Asif Rana, Mustafa Mukadam, S. Reza Ahmadzadeh, Sonia Chernova, Byron Boots

Reference:
Muhammad Asif Rana, Mustafa Mukadam, S. Reza Ahmadzadeh, Sonia Chernova and Byron Boots, "Skill
Generalization via Inference-Based Planning", In Proc. Robotics: Science and Systems (RSS),
Workshop on Mathematical Models, Algorithms, and Human-Robot Interaction, Boston, MA, USA, pp. 1--3,
12th-16th Jul. 2017.
Bibtex Entry:
@INPROCEEDINGS{rana2017skill, TITLE={Skill Generalization via Inference-Based Planning}, AUTHOR={Rana, Muhammad Asif and Mukadam, Mustafa and Ahmadzadeh, Seyed Reza and Chernova, Sonia and Boots, Byron}, BOOKTITLE={Robotics: Science and Systems ({RSS}), Workshop on Mathematical Models, Algorithms, and Human-Robot Interaction}, PAGES={1--3}, YEAR={2017}, MONTH={July}, ADDRESS={Boston, MA, USA}, }
Abstract:
We present a novel approach which unifies conventional learning from demonstration (LfD) and motion
planning using probabilistic inference, for generalizable skill reproduction. We also provide a new
probabilistic skill model that requires minimal parameter tuning, and is more suited for encoding
skill constraints and performing inference in an efficient manner. Experimental validation on a
manipulation skill is presented.

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