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Robot Manipulation and Learning
TopicLeading institutions, researchers & key papers
This cluster of papers focuses on robotic grasping, learning from demonstration, deep learning for object pose estimation, human-robot collaboration, and sensor-based robot systems. It explores topics such as dynamical movement primitives, impedance control, and safe interaction between humans and robots.
270
Works
IDs:OpenAlex
How has Robot Manipulation and Learning's publication output changed over time?
ScholarIQpublication output · 2004–2022
Output grew0% over the shown period — from 1 works in 2004 to 1 in 2022.
1
2
2
1
2
1
1
2
1
1
2004200720082010201120122016201920212022
What are the most-cited papers on Robot Manipulation and Learning?
ScholarIQmost cited works
On Learning, Representing, and Generalizing a Task in a Humanoid Robot
Sylvain Calinon, F. Guenter, Aude Billard
S4210170378. 20071,091 CitationsOPEN ACCESS
Robot Programming by Demonstration
Aude Billard, Sylvain Calinon, Rüdiger Dillmann, Stefan Schaal
2008985 CitationsOPEN ACCESS
Trends and challenges in robot manipulation
Aude Billard, Danica Kragić
Science. 2019960 CitationsOPEN ACCESS
Learning Stable Nonlinear Dynamical Systems With Gaussian Mixture Models
Seyed Mohammad Khansari-Zadeh, Aude Billard
IEEE Transactions on Robotics. 2011768 CitationsOPEN ACCESS
Recent Advances in Robot Learning from Demonstration
Harish Ravichandar, Athanasios Polydoros, Sonia Chernova, Aude Billard
S4210191328. 2019726 CitationsOPEN ACCESS
Where is Robot Manipulation and Learning research published, and who funds it?
ScholarIQvenues & funding sources
TOP JOURNALS
TOP FUNDERS
National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
Funder breakdown is a member featureSign up free to unlock
How much of the research on Robot Manipulation and Learning is open access?
ScholarIQopen access share
67%OPEN ACCESS
Gold
7%
Green
53%
Hybrid
0%
Bronze
7%
Closed
33%
Related on ScholarIQ
The central nervous system stabilizes unstable dynamics by learning optimal impedance
Paper
On Learning, Representing, and Generalizing a Task in a Humanoid Robot
Paper
Robot Programming by Demonstration
Paper
Trends and challenges in robot manipulation
Paper
Learning Stable Nonlinear Dynamical Systems With Gaussian Mixture Models
Paper
Recent Advances in Robot Learning from Demonstration
Paper