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

- Source: arXiv cs.RO
- Published: 2026-10-28T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/u9w4wjhl5gjrejcj958urui8v
- Original: https://arxiv.org/abs/2610.37170

## Summary

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.