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How Aloha Works


Data Collection

It all starts with data. Begin your project by either collecting training data yourself or downloading pre-existing training data sets. These data sets will provide the machine learning models with “experience” to train and inform the ML model for performing tasks.



Repeatedly perform individual tasks in a variety of ways. An example is trying to pick up a colored cube placed in multiple locations and from a variety of angles.


To save time, you can use publically available training data provided by the community and Trossen Robotics.

Hugging Face

We have partnered with Hugging Face as Aloha's community data-sharing platform. 

Data Structure

Multi-View Video Streams
Joint Speed (rad/sec)
Joint Position (rad)
Per Time Step (50Hz)


Train & Evaluate

Once you have a significant training data set, it’s time to begin the cyclical process of training and evaluating. You begin with the pre-loaded ACT++ Machine Learning Model, adjusting parameters and evaluating the success rate of your data inputs to task outputs.

ML Model Training

Training can be done on a variety of hardware platforms including the Aloha pre-loaded laptop, high-performance edge computing nodes, or even cloud computing.

Pre-loaded Laptop
Edge Computing
Cloud Computing