This project provides a training toolchain for adapting TienKung humanoid robots and RoboMIND dataset with the open-source LeRobot framework.
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Updated
Jun 12, 2026 - Python
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robotics-pipeline
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TraceOS standardizes AI experiments into reproducible, searchable, and comparable assets. One command runs experiments, generates reports, and produces structured analysis: capability vectors, failure taxonomy, and recommendations. Every run is tracked, traceable, and comparable. Built on ABC-130K (amazon-far/abc). Apache 2.0.
imitation-learning model-evaluation robot-learning benchmarking-framework behavior-cloning failure-analysis training-pipeline experiment-management experiment-automation vision-language-action ai-research-tool reproducible-ml robotics-pipeline ai-experiment-tracking ml-experiment-pipeline experiment-comparison experiment-lifecycle ml-experiment-analytics open-source-ml-tool python-experiment-runner
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Updated
Jul 3, 2026 - Python
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