TY - JOUR
T1 - Automatic sequencing of ballet poses
AU - Laviers, Amy
AU - Chen, Yushan
AU - Belta, Calin
AU - Egerstedt, Magnus
N1 - Funding Information:
The work by LaViers and Egerstedt is supported by the U.S. National Science Foundation through grant number 0757317. The work by Chen and Belta is supported by ONR MURI N00014-09-1051, ARO W911NF-09-1-0088, AFOSR YIP FA9550-09-1-020, and NSF CNS-0834260.
PY - 2011/9
Y1 - 2011/9
N2 - Understanding human behavior is a goal in many disciplines: behavioral psychology, neuroscience, robotics, computer vision, artificial intelligence, athletics, and dance, to name a few. Thus, this article may be understood in terms of a larger dialogue about how to represent human movement with a concise parameterization. Formal methods for verification can play a surprising role in this discourse. We will ensure that our system evolves according to specific style-based guidelines in a framework where verification methods become an integral part of the system model itself.
AB - Understanding human behavior is a goal in many disciplines: behavioral psychology, neuroscience, robotics, computer vision, artificial intelligence, athletics, and dance, to name a few. Thus, this article may be understood in terms of a larger dialogue about how to represent human movement with a concise parameterization. Formal methods for verification can play a surprising role in this discourse. We will ensure that our system evolves according to specific style-based guidelines in a framework where verification methods become an integral part of the system model itself.
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U2 - 10.1109/MRA.2011.942118
DO - 10.1109/MRA.2011.942118
M3 - Article
AN - SCOPUS:80052911934
SN - 1070-9932
VL - 18
SP - 87
EP - 95
JO - IEEE Robotics and Automation Magazine
JF - IEEE Robotics and Automation Magazine
IS - 3
M1 - 6016594
ER -