Synthesizing object receiving motions of humanoid robots with human motion database
By Katsu Yamane, Marcel Revfi, Tamim Asfour. 2013
47 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Control and Systems Engineering, Robotics & Control
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Ashutosh Saxena
- Thorsten Joachims
- Luc Van Gool
- Ashesh Jain
- Abhinav Kumar Gupta
- Kristen Grauman
- Li Fei-Fei
- Dacheng Tao
In Control and Systems Engineering
- Ashesh Jain
- Thorsten Joachims
- Shikhar Sharma
- Brian Wojcik
- Ashutosh Saxena
- Sergey Levine
- Pieter Abbeel
- Abhinav Kumar Gupta
In Robotics & Control
- Ashesh Jain
- Thorsten Joachims
- Brian Wojcik
- Shikhar Sharma
- Ashutosh Saxena
- Andrew Y. Ng
- Sergey Levine
- Hema Swetha Koppula
Citations in the corpus
- Learning Trajectory Preferences for Manipulators via Iterative Improvement (2013, methodology): “[8] used functional gradients [29] to optimize for legibility of robot trajectories.”
- Learning preferences for manipulation tasks from online coactive feedback (2015, background): “ional manipulators. For computational reasons they create a database of prior trajectories, which we could leverage to train our system. Other recent works consider generating human-like trajectories [15, 14, 58]. Humans-robot interaction is an important aspect and our approach could incorporate sim”