563 citations · 646 across the 8 of their papers we have counts for
5 papers · 1 filter
Multi-View Fusion for Multi-Level Robotic Scene Understanding
Yunzhi Lin, Jonathan Tremblay, Stephen Tyree +2
We present a system for multi-level scene awareness for robotic manipulation. Given a sequence of camera-in-hand RGB images, the system calculates three types of information: 1) a…
Indirect Object-to-Robot Pose Estimation from an External Monocular RGB Camera
Jonathan Tremblay, Stephen Tyree, Terry Mosier +1
We present a robotic grasping system that uses a single external monocular RGB camera as input. The object-to-robot pose is computed indirectly by combining the output of two neura…
How to Close Sim-Real Gap? Transfer with Segmentation!
Mengyuan Yan, Qingyun Sun, Iuri Frosio +2
One fundamental difficulty in robotic learning is the sim-real gap problem. In this work, we propose to use segmentation as the interface between perception and control, as a domai…
Synthetically Trained Neural Networks for Learning Human-Readable Plans from Real-World Demonstrations
Jonathan Tremblay, Thang To, Artem Molchanov +3
We present a system to infer and execute a human-readable program from a real-world demonstration. The system consists of a series of neural networks to perform perception, program…
Sim-to-Real Transfer of Accurate Grasping with Eye-In-Hand Observations and Continuous Control
Mengyuan Yan, Iuri Frosio, Stephen Tyree +1
In the context of deep learning for robotics, we show effective method of training a real robot to grasp a tiny sphere (1.37cm of diameter), with an original combination of system…