ProDMP: A Unified Perspective on Dynamic and Probabilistic Movement Primitives-Reference-Cited by-同舟云学术

ProDMP: A Unified Perspective on Dynamic and Probabilistic Movement Primitives

Published:2023-04 Issue:4 Volume:8 Page:2325-2332
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Li Ge¹^ORCID,Jin Zeqi¹,Volpp Michael¹^ORCID,Otto Fabian²^ORCID,Lioutikov Rudolf¹,Neumann Gerhard¹

Affiliation:

1. Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology, Karlsruhe, Germany

2. Bosch Center for Artificial Intelligence, Robert-Bosch-Campus 1, Renningen, Germany

Funder

Carl Zeiss Foundation through the Project JuBot

Helmholtz Association of German Research Centers

State of Baden-Württemberg through bwHPC

Deutsche Forschungsgemeinschaft

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7083369/10049284/10050558.pdf?arnumber=10050558

Reference29 articles.

1. Conditional neural movement primitives;seker;Proc Robot Sci Syst,0

2. Using probabilistic movement primitives in robotics

3. Dynamic movement primitives in robotics: A tutorial survey;saveriano,2021

4. Learning Replanning Policies With Direct Policy Search

5. Neural dynamic policies for end-to-end sensorimotor learning;bahl;Proc Adv Neural Inf Process Syst,0

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