A Hand-Centric Classification of Human and Robot Dexterous Manipulation

By Ian M. Bullock, Raymond R. Ma, Aaron M. Dollar. 2013

216 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Cognitive Neuroscience, Control and Systems Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Sergey Levine
2. Vikash Kumar
3. Abhishek Gupta
4. Aravind Rajeswaran
5. Henry Zhu
6. Danica Kragic
7. Aaron M. Dollar
8. Pieter Abbeel

In Cognitive Neuroscience

1. Abhishek Gupta
2. Sergey Levine
3. Aravind Rajeswaran
4. Vikash Kumar
5. Danica Kragic
6. Chelsea Finn
7. Pieter Abbeel
8. Aviral Kumar

In Control and Systems Engineering

1. Sergey Levine
2. Vikash Kumar
3. Abhishek Gupta
4. Aravind Rajeswaran
5. Pieter Abbeel
6. Chelsea Finn
7. Henry Zhu
8. Danica Kragic

Citations in the corpus

• Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost (2018, background): “work is often focused on achieving stable grasps by explicitly reasoning about the stability of the grasp using geometric and analytic metrics [6], [7], [8].”
• The GRASP Taxonomy of Human Grasp Types (2016, background): “[24], our classification excludes the whole nonprehensile category (category: C NP), because the environment provides the reaction force in those grasps.”