ACT — ALOHA Single-Arm (Left) — 40k steps (SHIPPED)
Action Chunking Transformer (ACT) policy for a single-arm (LEFT) Trossen ALOHA manipulation task — autonomous O2 mask placement on a human surrogate (MEDEVAC-inspired).
This is the production-shipped retrain at 40,000 steps (workstream S003). It supersedes the initial 13.4k baseline at JHeisler/aloha_solo_left_4_6_26_act_left. Same architecture, same dataset, ~3× the gradient updates and ~3× the data exposure.
Training Config
| Field | Value |
|---|---|
| Architecture | ACT (ResNet18 backbone + 4-layer Transformer encoder + VAE chunking head) |
| Dataset | JHeisler/aloha_solo_left_4_6_26 — 50 episodes, 29,785 samples, 30 fps |
| State / action dim | 9 / 9 |
| Cameras | cam_high, cam_left_wrist (3×480×640 each) |
| Steps | 40,000 |
| Batch size | 48 |
| Learning rate | 6e-5 (linear warmup 500 → cosine) |
| Total samples seen | |
| AMP | enabled |
| torch.compile | enabled |
| Save freq | every 10,000 steps (10k / 20k / 30k / 40k checkpoints) |
| Final loss | ~0.015 |
| Final grad norm | ~0.19 |
| Wall clock | ~6h 7min on RTX A4500 |
| LeRobot pin | 96c7052777aca85d4e55dfba8f81586103ba8f61 |
Why retrained at 40k?
The initial 13.4k run (S001) trained for 21 epochs and showed signs of underfit on real-robot evaluation (gripper timing + distance judgement failures). 40k is a pragmatic step-up (64 epochs) without committing to the full original 80k Colab budget; loss converged to roughly half (0.029 → 0.015) with ¼ the grad norm.
Project Lineage
| Workstream | Model | Steps | Samples | HF |
|---|---|---|---|---|
| S001 | ACT | 13,400 | 640K | act_left |
| S002 | Hybrid ACT+Diffusion | 13,400 | 321K | act_diffusion |
| S003 | ACT (shipped) | 40,000 | 1.92M | this repo |
| S004 | Hybrid ACT+Diffusion | 40,000 | 1.12M | act_diffusion_40k |
Usage
from lerobot.common.policies.act.modeling_act import ACTPolicy
policy = ACTPolicy.from_pretrained("JHeisler/aloha_solo_left_4_6_26_act_left_40k")
Citation / Course
EN.525.681 school project — JHU Whiting School of Engineering. Team: Jake Heisler, Laura Kroening, Purushottam Shukla.
Code reference: HuggingFace LeRobot at commit 96c7052.
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