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Data-Scale Comparison of ACT, Diffusion Policy, SmolVLA, and π0.5 on a Low-Cost Robotic Arm

Researchers trained four imitation-learning policies—ACT, Diffusion Policy, SmolVLA, and π0.5—on a low-cost SO-101 robotic arm using 12 to 200 teleoperated demonstrations, evaluating 1,340 episodes in total.

Part of the event: Comparison of Data Scale for Four Imitation Learning Strategies on a Low-Cost Robotic Arm

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