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Robot Manipulation and Learning

TopicLeading institutions, researchers & key papers

Robot Manipulation and Learning is a topic indexed in ScholarIQ from OpenAlex.

What is known about Robot Manipulation and Learning?

ScholarIQrecord summary

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.

How many works does Robot Manipulation and Learning have?

ScholarIQindexed works

Robot Manipulation and Learning has 270 works in the ScholarIQ index. The count is the OpenAlex total, not the number of papers listed on this page.

What is the OpenAlex record for Robot Manipulation and Learning?

ScholarIQopenalex

The OpenAlex for Robot Manipulation and Learning is on the source record.

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
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 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
Annual Review of Control Robotics and Autonomous Systems. 2019726 CitationsOPEN ACCESS

Where is Robot Manipulation and Learning research published, and who funds it?

ScholarIQvenues & funding sources

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%

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