Learning from demonstration with partially observable task parameters using dynamic movement primitives and Gaussian process regression

2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM) ◽

10.1109/aim.2016.7576881 ◽

2016 ◽

Author(s):

Tohid Alizadeh ◽

Milad Malekzadeh ◽

Soheila Barzegari

Keyword(s):

Gaussian Process ◽

Gaussian Process Regression ◽

Learning From Demonstration ◽

Movement Primitives ◽

Dynamic Movement ◽

Dynamic Movement Primitives ◽

Partially Observable ◽

Task Parameters

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Learning from demonstration using improved dynamic movement primitives

10.1109/iciea51954.2021.9516425 ◽

2021 ◽

Author(s):

Tiantian Wang ◽

Liang Yan ◽

Gang Wang ◽

Xiaoshan Gao ◽

Nannan Du ◽

...

Keyword(s):

Learning From Demonstration ◽

Movement Primitives ◽

Dynamic Movement ◽

Dynamic Movement Primitives

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Learning and Generalization of Dynamic Movement Primitives by Hierarchical Deep Reinforcement Learning from Demonstration

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) ◽

10.1109/iros.2018.8594476 ◽

2018 ◽

Author(s):

Wonchul Kim ◽

Chungkeun Lee ◽

H. Jin Kim

Keyword(s):

Reinforcement Learning ◽

Learning From Demonstration ◽

Movement Primitives ◽

Dynamic Movement ◽

Dynamic Movement Primitives

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The Generalization of Robot Skills Based on Dynamic Movement Primitives

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2021.04.105 ◽

2020 ◽

Vol 53 (5) ◽

pp. 265-270

Author(s):

Xian Li ◽

Chenguang Yang ◽

Ying Feng

Keyword(s):

Movement Primitives ◽

Dynamic Movement ◽

Dynamic Movement Primitives

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Overcoming some drawbacks of Dynamic Movement Primitives

Robotics and Autonomous Systems ◽

10.1016/j.robot.2021.103844 ◽

2021 ◽

pp. 103844

Author(s):

Michele Ginesi ◽

Nicola Sansonetto ◽

Paolo Fiorini

Keyword(s):

Movement Primitives ◽

Dynamic Movement ◽

Dynamic Movement Primitives

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Incremental Motor Skill Learning and Generalization from Human Dynamic Reactions based on Dynamic Movement Primitives and Fuzzy Logic System

IEEE Transactions on Fuzzy Systems ◽

10.1109/tfuzz.2021.3136933 ◽

2021 ◽

pp. 1-1

Author(s):

Zhenyu Lu ◽

Ning Wang ◽

Miao Li ◽

Chenguang Yang

Keyword(s):

Fuzzy Logic ◽

Motor Skill ◽

Fuzzy Logic System ◽

Skill Learning ◽

Motor Skill Learning ◽

Movement Primitives ◽

Dynamic Movement ◽

Dynamic Movement Primitives ◽

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A real-time nearly time-optimal point-to-point trajectory planning method using dynamic movement primitives

2014 23rd International Conference on Robotics in Alpe-Adria-Danube Region (RAAD) ◽

10.1109/raad.2014.7002244 ◽

2014 ◽

Author(s):

Klemens Springer ◽

Hubert Gattringer ◽

Christoph Stoger

Keyword(s):

Real Time ◽

Trajectory Planning ◽

Planning Method ◽

Optimal Point ◽

Movement Primitives ◽

Dynamic Movement ◽

Time Optimal ◽

Dynamic Movement Primitives ◽

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Dimensionality Reduction for Dynamic Movement Primitives and Application to Bimanual Manipulation of Clothes

IEEE Transactions on Robotics ◽

10.1109/tro.2018.2808924 ◽

2018 ◽

Vol 34 (3) ◽

pp. 602-615 ◽

Author(s):

Adria Colome ◽

Carme Torras

Keyword(s):

Dimensionality Reduction ◽

Movement Primitives ◽

Dynamic Movement ◽

Dynamic Movement Primitives

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Dynamic Movement Primitives Plus: For enhanced reproduction quality and efficient trajectory modification using truncated kernels and Local Biases

2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) ◽

10.1109/iros.2016.7759554 ◽

2016 ◽

Author(s):

Ruohan Wang ◽

Yan Wu ◽

Wei Liang Chan ◽

Keng Peng Tee

Keyword(s):

Movement Primitives ◽

Dynamic Movement ◽

Dynamic Movement Primitives

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An adaptive learning and control framework based on Dynamic Movement Primitives with application to human–robot handovers

Robotics and Autonomous Systems ◽

10.1016/j.robot.2021.103935 ◽

2021 ◽

pp. 103935

Author(s):

Min Wu ◽

Bertram Taetz ◽

Yanhao He ◽

Gabriele Bleser ◽

Steven Liu

Keyword(s):

Adaptive Learning ◽

Movement Primitives ◽

Dynamic Movement ◽

Control Framework ◽

Dynamic Movement Primitives ◽

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Learning Parametric Dynamic Movement Primitives from Multiple Demonstrations

Neural Information Processing. Theory and Algorithms - Lecture Notes in Computer Science ◽

10.1007/978-3-642-17537-4_43 ◽

2010 ◽

pp. 347-354 ◽

Author(s):

Takamitsu Matsubara ◽

Sang-Ho Hyon ◽

Jun Morimoto

Keyword(s):

Movement Primitives ◽

Dynamic Movement ◽

Dynamic Movement Primitives

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