act_so101_rubik_v2 is an open-source robotics policy based on imitation learning and action chunking with transformers. It enables robots to learn and perform complex tasks by predicting short action sequences from teleoperated data. The model is suitable for robotics researchers and developers seeking advanced control policies.
Act So101 Rubik is an Other AI product. It focuses on enabling robots to efficiently learn and execute complex tasks through imitation learning and action chunking. It is built as an open-source project for robotics researchers and developers. Act So101 Rubik is open source under the Apache-2.0 license. Act So101 Rubik is available on the web, API, and the command line, and it can be self-hosted.
It is developed by sirius-lerobot, and the product first shipped in 2024. Development happens publicly on GitHub with 25.7k stars and 164 commits in the last 90 days. PulseGate's similarity index finds few close equivalents — Act So101 Rubik occupies a relatively distinct niche. Key capabilities include imitation learning, robotics policy, and action chunking.
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