Using Near-Field Stereo Vision for Robotic Grasping in Cluttered Environments

By A. Leeper, Kaijen Hsiao, Eric King-Wah Chu, J. Salisbury. 2010

28 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Biomedical Engineering, 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 Aerospace Engineering

1. Peter Pastor
2. Deirdre Quillen
3. Sergey Levine
4. Alex Krizhevsky
5. Pieter Abbeel
6. Chelsea Finn
7. Vikash Kumar
8. Abhinav Kumar Gupta

In Biomedical Engineering

1. Sergey Levine
2. Peter Pastor
3. Deirdre Quillen
4. Alex Krizhevsky
5. Pieter Abbeel
6. Chelsea Finn
7. Lerrel Pinto
8. Abhinav Kumar Gupta

In Control and Systems Engineering

1. Sergey Levine
2. Peter Pastor
3. Pieter Abbeel
4. Chelsea Finn
5. Deirdre Quillen
6. Alex Krizhevsky
7. Abhinav Kumar Gupta
8. Lerrel Pinto

Citations in the corpus

• Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection (2016, background): “Many practical grasping systems use a wrist-mounted camera to address this issue (Leeper et al., 2014).”
• Learning Hand-Eye Coordination for Robotic Grasping with Large-Scale Data Collection (2016, methodology): “Many practical grasping systems use a wrist-mounted camera to address this issue [Leeper et al., 2014].”