4 papers · 1 filter
Camera-to-Robot Pose Estimation from a Single Image
Timothy E. Lee, Jonathan Tremblay, Thang To +5
We present an approach for estimating the pose of an external camera with respect to a robot using a single RGB image of the robot. The image is processed by a deep neural network…
Toward Sim-to-Real Directional Semantic Grasping
Shariq Iqbal, Jonathan Tremblay, Thang To +6
We address the problem of directional semantic grasping, that is, grasping a specific object from a specific direction. We approach the problem using deep reinforcement learning vi…
Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objects
Jonathan Tremblay, Thang To, Balakumar Sundaralingam +3
Using synthetic data for training deep neural networks for robotic manipulation holds the promise of an almost unlimited amount of pre-labeled training data, generated safely out o…
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…