act-hyak-test is an open-source imitation learning model for robotics, designed to predict action chunks from teleoperated data. It enables researchers and developers to run local inference and integrate advanced policy models into robotics workflows.
In the Other AI space, Act Hyak Test takes a focused approach. It focuses on providing an open-source imitation learning model for robotics action chunking and policy inference. Act Hyak Test 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 the command line, and it can be self-hosted.
Behind Act Hyak Test is HuskyMango, and the product first shipped in 2024. The project is developed in the open on GitHub with 25.8k stars and 163 commits in the last 90 days. Across PulseGate's embedding index, Act Hyak Test has few near neighbours, marking it as relatively distinct. Among its 5 catalogued features are imitation learning, action chunking, and robotics policy.
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HuskyMango/act-hyak-test discovered by the PulseGate indexer
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