Fine-tuning π0.5 on a real manufacturing task: <1 hour of DAgger data drove big success-rate gains

DominiqueCAPaul · x · 2026-09-25

Robotics researcher DominiqueCAPaul published a blog with empirical results fine-tuning π0.5 on a real manufacturing task. Key findings: less than 1 hour of DAgger-style human intervention data significantly boosted task success rate, and scene diversity plus data quality mattered more than volume. The post is making rounds in the robot learning community.

Related event: Dream Machines' π0.5 fine-tuning ablation hits 98% success: data quality beats scale(9 posts)→

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