GitHub / Unity-Technologies / Robotics-Object-Pose-Estimation
A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.
Stars: 321
Forks: 78
Open issues: 7
License: apache-2.0
Language: Python
Size: 38.6 MB
Dependencies parsed at:
3
Created at: over 4 years ago
Updated at: 8 days ago
Pushed at: about 3 years ago
Last synced at: 3 days ago
Topics: autonomy, computer-vision, deep-learning, machine-learning, manipulation, model-training, motion-planning, perception, physics-simulation, pose-estimation, robotics, robotics-simulation, ros, simulation, synthetic-data, trajectory-generation, tutorial, unity, ur3-robot-arm, urdf
- easydict ==1.9
- kfp ==1.0.4
- tensorboardX ==2.1