bluecube_101_0716_policy is an open-source imitation learning policy model for robotics, trained using the Action Chunking with Transformers (ACT) method. It predicts short action chunks from teleoperated data, allowing developers and researchers to run, evaluate, or further train the policy for robotics applications. The model is distributed under the Apache-2.0 license and can be integrated with robotics frameworks such as LeRobot.
Bluecube 101 0716 Policy sits in PulseGate's Other AI category. Enabling developers to implement and experiment with imitation learning policies for robotics tasks without building models from scratch. Bluecube 101 0716 Policy is an open-source project aimed at robotics researchers and developers. The project is open source (Apache-2.0). The product ships for the web and API, and it can be self-hosted.
Behind Bluecube 101 0716 Policy is JunJunJunya, and the product first shipped in 2024. The project is developed in the open on GitHub with 25.9k stars. Among its 5 catalogued features are imitation learning, action chunking, and transformer-based.
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