Vision-Based Reaching Using Modular Deep Networks: from Simulation to the Real World
By Fangyi Zhang, Jürgen Leitner, Ben Upcroft, Peter Corke. 2016
18 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, 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
- Luc Van Gool
- Sergey Levine
- Pieter Abbeel
- Abhinav Kumar Gupta
- Jitendra Malik
- Trevor Darrell
- Dacheng Tao
- Lei Tai
In Robotics & Control
- Pieter Abbeel
- Lerrel Pinto
- Sergey Levine
- Lei Tai
- Marcin Andrychowicz
- Wojciech Zaremba
- Peter Welinder
- Chelsea Finn
Citations in the corpus
- Asymmetric Actor Critic for Image-Based Robot Learning (2017, background): “Another approach is domain adaptation from the simulator [5]–[10], since it may be easier to finetune from a simulator policy than training in the real world.”
- Deep-learning in Mobile Robotics - from Perception to Control Systems: A Survey on Why and Why not (2016, methodology): “Tensegrity (Geng et al., 2016) (Levine et al., 2016a) UAV control (Zhang et al., 2016c) legged locomotion and cartpole swing-up.”