Learning from demonstration with partially observable task parameters using Dynamic Movement Primitives and Gaussian Process Regression

Alizadeh T, Malekzadeh M, Barzegari S (2016)
Presented at the IEEE International Conference on Advanced Intelligent Mechatronics (AIM) 2016, Banff, Canada.

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IEEE International Conference on Advanced Intelligent Mechatronics (AIM) 2016
Location
Banff, Canada
Conference Date
2016-07-12 – 2016-07-15
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Alizadeh T, Malekzadeh M, Barzegari S. Learning from demonstration with partially observable task parameters using Dynamic Movement Primitives and Gaussian Process Regression. Presented at the IEEE International Conference on Advanced Intelligent Mechatronics (AIM) 2016, Banff, Canada.
Alizadeh, T., Malekzadeh, M., & Barzegari, S. (2016). Learning from demonstration with partially observable task parameters using Dynamic Movement Primitives and Gaussian Process Regression. Presented at the IEEE International Conference on Advanced Intelligent Mechatronics (AIM) 2016, Banff, Canada. doi:10.1109/AIM.2016.7576881
Alizadeh, T., Malekzadeh, M., and Barzegari, S. (2016).“Learning from demonstration with partially observable task parameters using Dynamic Movement Primitives and Gaussian Process Regression”. Presented at the IEEE International Conference on Advanced Intelligent Mechatronics (AIM) 2016, Banff, Canada.
Alizadeh, T., Malekzadeh, M., & Barzegari, S., 2016. Learning from demonstration with partially observable task parameters using Dynamic Movement Primitives and Gaussian Process Regression. Presented at the IEEE International Conference on Advanced Intelligent Mechatronics (AIM) 2016, Banff, Canada.
T. Alizadeh, M. Malekzadeh, and S. Barzegari, “Learning from demonstration with partially observable task parameters using Dynamic Movement Primitives and Gaussian Process Regression”, Presented at the IEEE International Conference on Advanced Intelligent Mechatronics (AIM) 2016, Banff, Canada, 2016.
Alizadeh, T., Malekzadeh, M., Barzegari, S.: Learning from demonstration with partially observable task parameters using Dynamic Movement Primitives and Gaussian Process Regression. Presented at the IEEE International Conference on Advanced Intelligent Mechatronics (AIM) 2016, Banff, Canada (2016).
Alizadeh, Tohid, Malekzadeh, Milad, and Barzegari, Soheila. “Learning from demonstration with partially observable task parameters using Dynamic Movement Primitives and Gaussian Process Regression”. Presented at the IEEE International Conference on Advanced Intelligent Mechatronics (AIM) 2016, Banff, Canada, 2016.
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