Repository
Research
Diffusion Policy
A visuomotor policy approach using diffusion to generate robot actions.
Robot policies
Models / Research
CLIPort
A language-conditioned framework for visual pick-and-place policies.
Overview
A language-conditioned framework for visual pick-and-place policies.
Compare observation inputs, action representations, adaptation data and inference requirements. Code licensing and model-weight licensing may differ; review both before deployment. A source repository may have an open code license while its checkpoints have separate terms.
Project information
- Maintainer
- cliport
- Primary language
- Jupyter Notebook
- Repository code license
- Apache-2.0
- Model-weight license
- Not recorded
- Dataset license
- Not recorded
- Hardware design license
- Not recorded
- Maintenance
- Not archived in the last recorded metadata
- Last observed repository push
- 2023-11-02
Code licenses do not automatically cover model weights, datasets or hardware designs. Unrecorded license details require confirmation with the publisher.
Documentation sections
- CLIPort
- Guides
- Installation
- setup virtualenv with whichever package manager you prefer
- Quickstart
- Download
Browse this resource’s categories
Explore related collections
Browse Models →More in Models
Repository
Research
Website
Research
openpi
Code and model resources for Physical Intelligence robot policies.
Vision-language-action
Repository
Research
NVIDIA Isaac GR00T
Robot foundation-model resources for humanoid learning workflows.
Vision-language-action
Repository
Research
Octo
A generalist robot policy framework for adapting across manipulation tasks.
Robot policies
Repository
Research
alpamayo1.5 · NVlabs
NVIDIA Alpamayo 1.5 Nano is an open 10B reasoning VLA model for autonomous vehicles with reinforcement-learning enhanced reasoning, navigation guidance, and visual question answering.
Vision-language-action
Repository
Research
iros20 6d pose tracking · wenbowen123
se(3)-TrackNet provides 6D object-pose tracking research and visual-feedback-control examples.
Perception models