grasp_redblock_act_c100_a100_50k_v2 is an open-source imitation learning model for robotics, trained to predict action chunks from teleoperated data. It is designed for robotics researchers seeking to implement advanced policy learning and action chunking in robotic systems.
Grasp Redblock Act C100 A100 50k sits in PulseGate's Other AI category. It focuses on enabling robots to learn and execute complex actions through imitation learning and action chunking. It is built as an open-source project for robotics researchers. Grasp Redblock Act C100 A100 50k is open source under the Apache-2.0 license. The product ships for the web and the command line.
It is developed by eslab1234, and the product first shipped in 2024. Development happens publicly on GitHub with 25.8k stars and 157 commits in the last 90 days. PulseGate's similarity index finds few close equivalents — Grasp Redblock Act C100 A100 50k occupies a relatively distinct niche. Key capabilities include imitation learning, robotic policy, and action chunking.
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eslab1234/grasp_redblock_act_c100_a100_50k_v2 discovered by the PulseGate indexer
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