dimensionalOS / dimensionalOS/dimos
Train an ACT policy to make the highest pile possible
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manipulation
- Dominant language
- Python
- Stars
- 4.5k
- Forks
- 808
- Avg merge
- 3d 5h
- Merged PRs (30d)
- 233
Description
Demos:
- Ask it to make shapes like circles, lines etc - with agent input and arms execute
Synced from DIM-1477 by mustafa
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by clarifying the ACT policy objective and the shape-making and highest-pile demos described in the issue. Identify the existing policy-training entry point, robot or arm interface, and available data before estimating the work. Done should include a reproducible trained policy and demonstrated arm behavior for the agreed task.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning, robotics
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100