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Generalized Cylinders for Learning, Reproduction, Generalization, and Refinement of Robot Skills

posted Jun 5, 2017, 10:26 AM by Reza Ahmadzadeh   [ updated Jul 4, 2017, 4:30 PM ]
S. Reza Ahmadzadeh, Muhammad Asif Rana, Sonia Chernova

S. Reza Ahmadzadeh, Muhammad Asif Rana, Sonia Chernova, "Generalized Cyliners for Learning,
Reproduction, Generalization, and Refinement of Robot Skills", In Proc. Robotics: Science and
Systems (RSS 2017), Massachusetts Institute of Technology in Cambridge, Massachusetts, USA,
12th-16th Jul. 2017.
Bibtex Entry:
@INPROCEEDINGS{ahmadzadeh2017generalized, TITLE={Generalized Cylinders for Learning, Reproduction,Generalization, and Refinement of Robot Skills}, AUTHOR={Ahmadzadeh, S. Reza and Rana Muhammad Asif and Chernova, Sonia}, BOOKTITLE={Robotics: Science and Systems ({RSS})}, YEAR={2017}, MONTH={July}, PAGES={1--10}, ADDRESS={Boston, MA, USA} }
This paper presents a novel geometric approach for learning and reproducing trajectory-based skills
from human demonstrations. Our approach models a skill as a Generalized Cylinder, a geometric
representation composed of an arbitrary space curve called spine and a smoothly varying
cross-section. While this model has been utilized to solve other robotics problems, this is the
first application of Generalized Cylinders to manipulation. The strengths of our approach are the
model’s ability to identify and extract the implicit characteristics of the demonstrated skill,
support for reproduction of multiple trajectories that maintain those characteristics,
generalization to new situations through nonrigid registration, and interactive human refinement of
the resulting model through kinesthetic teaching. We validate our approach through several
real-world experiments with a Jaco 6-DOF robotic arm.

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