Adapting Object-Centric Probabilistic Movement Primitives with Residual Reinforcement Learning
Author:
Affiliation:
1. Institute for Intelligent Autonomous Systems,TU Darmstadt (TUDa),Computer Science Department
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9999736/9999739/10000148.pdf?arnumber=10000148
Reference46 articles.
1. Learning assembly tasks in a few minutes by combining impedance control and residual recurrent reinforcement learning;kulkarni;Advanced Intelligent Systems,2021
2. ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows
3. Residual reinforcement learning from demonstrations;alakuijala;ArXiv Preprint,2021
4. Kernelized movement primitives
5. Variable Impedance Control in End-Effector Space: An Action Space for Reinforcement Learning in Contact-Rich Tasks
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1. Robot Learning Method for Human-like Arm Skills Based on the Hybrid Primitive Framework;Sensors;2024-06-19
2. Extended residual learning with one-shot imitation learning for robotic assembly in semi-structured environment;Frontiers in Neurorobotics;2024-04-29
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