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Robotics-Object-Pose-Estimation · Unity-Technologies

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…

perception geometry
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Robotics-Object-Pose-Estimation · Unity-Technologies resource page screenshot
Resource screenshot · captured 2026-10-09 · visually reviewed

Overview

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…

Publisher purpose: 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.

Inspect installation instructions, supported versions, examples and interfaces in the source. This directory does not claim the software has been installed or tested on your robot.

Project information

Maintainer
Unity-Technologies
Primary language
Python
Repository code license
Apache-2.0
Model-weight license
Not recorded
Dataset license
Not recorded
Hardware design license
Not recorded
Maintenance
Not archived in the last recorded metadata
Last observed repository push
2022-04-13

Code licenses do not automatically cover model weights, datasets or hardware designs. Unrecorded license details require confirmation with the publisher.

Documentation sections

  • Object Pose Estimation Demo
  • <a name="link-part-1">[Part 1: Create Unity Scene with Imported URDF](Documentation/1_set_up_the_scene.md)</a>
  • <a name="link-part-2">[Part 2: Setup the Scene for Data Collection](Documentation/2_set_up_the_data_collection_scene.md)</a>
  • <a name="link-part-3">[Part 3: Data Collection and Model Training](Documentation/3_data_collection_model_training.md)</a>
  • <a name="link-part-4">[Part 4: Pick-and-Place](Documentation/4_pick_and_place.md)</a>
  • Support

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