| --- |
| license: mit |
| pretty_name: ACT action chunking study, per-episode results |
| tags: |
| - robotics |
| - lerobot |
| - act |
| - aloha |
| - evaluation |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # ACT action chunking under delay and disturbance: per-episode results |
|
|
| This repository holds the raw outputs of the study |
| [ACT action chunking under delay and disturbance](https://github.com/DiyunZ/act-chunking-study). |
| Every simulated episode behind the study's tables is stored as one JSON record. The repository also |
| holds the scripts that the Hugging Face Jobs ran. |
|
|
| - `code/scripts/` holds the scripts as uploaded for the jobs. The GitHub repository is the maintained copy. |
| - `results/<run>/meta.json` holds the settings of a run: grid, seeds, deterministic kernels, displacement window, checkpoint, versions and GPU. |
| - `results/<run>/<condition>/seeds_<first>-<last>.json` holds one block of 25 seeds for one condition, under the key `episodes`. |
|
|
| The task is ALOHA transfer cube (gym-aloha), 400 steps at 50 Hz. The checkpoints are the official |
| [lerobot/act_aloha_sim_transfer_cube_human](https://huggingface.co/lerobot/act_aloha_sim_transfer_cube_human) |
| ("official") and a retrained [FTG64/act_aloha_transfer_cube](https://huggingface.co/FTG64/act_aloha_transfer_cube) |
| ("ours"). |
|
|
| ## Runs |
|
|
| | Run | Checkpoint | Contents | |
| | --- | --- | --- | |
| | `validation_official` | official | Harness vs `lerobot-eval` on seeds 1000–1049 (`harness/`, `lerobot/`), a displacement check, and videos | |
| | `ckpt_ours_025000` to `ckpt_ours_100000` | ours at 25k to 100k steps | Full chunk, no delay, seeds 1000–1199 | |
| | `ckpt_official` | official | Full chunk, no delay, seeds 1000–1499 (the seeds of its published evaluation) | |
| | `noise_floor` | official | Repeated runs that measure GPU nondeterminism | |
| | `core_official`, `core_ours100k` | official, ours at 100k | 5 execution modes × (5 latencies + 3 displacements), seeds 1000–1199 | |
| | `diag_official`, `diag_ours100k` | official, ours at 100k | Arm trajectories for the first 200 steps (field `trajectory`), seeds 1000–1049 | |
| | `diag_te_official`, `diag_te_ours100k` | official, ours at 100k | The same trajectories for temporal ensembling: c = 0.01 without latency, c = −0.2 at 0 and 400 ms | |
| | `te_weights_official`, `te_weights_ours100k` | official, ours at 100k | Temporal ensembling with coefficients 0, −0.05, −0.1 and −0.2, seeds 1000–1199 | |
|
|
| ## Condition names |
|
|
| Condition names have the form `<mode>_d<delay>_m<displacement>`, for example `replan25_d00_m6`. |
|
|
| - The mode is `full` (the whole chunk), `replan50`, `replan25` or `replan10` (a new chunk every k |
| steps), `te` (temporal ensembling with ACT's default coefficient 0.01), or `te<c>` (coefficient c, |
| for example `te-0.05`). |
| - The delay is the observation latency in 20 ms control steps: 0, 2, 5, 10 or 20. |
| - The displacement is the distance in cm that the cube is moved, at a random step inside the run's |
| displacement window (in `meta.json`; 50–75 for the core, diagnostic and ensembling grids). |
|
|
| ## Episode fields |
|
|
| | Field | Meaning | |
| | --- | --- | |
| | `seed` | Environment seed. The displacement direction uses seed + 10000. | |
| | `success` | The cube was transferred to the left gripper (reward 4). | |
| | `max_reward` | Highest reward stage reached: 1 right gripper touches the cube, 2 lifted, 3 left gripper touches, 4 success. | |
| | `sum_reward` | Sum of the per-step rewards. | |
| | `first_step_at_reward` | First step at which each reward stage was reached. | |
| | `cube_start_xy` | Initial cube position in m. | |
| | `t_move`, `delta_m`, `moved_m` | Step of the displacement, its vector, and its length in m. | |
| | `reward_before_move` | Reward stage when the cube was moved (0 means not yet touched). | |
| | `arms_unchanged_by_move` | The move left the arm joints unchanged. | |
| | `mode`, `k`, `delay`, `displacement_cm` | The condition's settings. Later runs also record `te_coeff`. | |
|
|
| ## Load |
|
|
| ```python |
| import glob, json |
| |
| episodes = [e for f in glob.glob("results/core_ours100k/*/seeds_*.json") for e in json.load(open(f))["episodes"]] |
| ``` |
|
|
