robotics-diffusion-transformer
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license: mit
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# RDT-1B
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RDT-1B is a 1B-parameter imitation learning Diffusion Transformer pre-trained on 1M+ multi-robot episodes. Given a language instruction and 3-view RGB image observations, RDT can predict the next
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64 robot actions. RDT is inherently compatible with almost all kinds of modern mobile manipulators, from single-arm to dual-arm, joint to EEF, pos. to vel., and even with a mobile chassis.
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All the code and model weights are licensed under MIT license.
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Please refer to our [project page](
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## Model Details
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- **Developed by**
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- **License:** MIT
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- **Repository:** [
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- **Paper :** [
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- **Project Page:** https://rdt-robotics.github.io/rdt-robotics/
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## Uses
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RDT
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Please refer to [our repository](https://github.com/GeneralEmbodiedSystem/RoboticsDiffusionTransformer/blob/main/docs/pretrain.md) for all the above guides.
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license: mit
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language:
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- en
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# RDT-1B
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RDT-1B is a 1B-parameter imitation learning Diffusion Transformer pre-trained on 1M+ multi-robot episodes. Given a language instruction and 3-view RGB image observations, RDT can predict the next
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64 robot actions. RDT is inherently compatible with almost all kinds of modern mobile manipulators, from single-arm to dual-arm, joint to EEF, pos. to vel., and even with a mobile chassis.
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All the [code]() and pretrained model weights are licensed under MIT license.
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Please refer to our [project page](https://rdt-robotics.github.io/rdt-robotics/) and [paper]() for more information.
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## Model Details
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- **Developed by** RDT Team from Tsinghua University.
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- **License:** MIT
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- **Language(s) (NLP):** en
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- **Model Architecture:** Diffusion Transformer.
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- **Pretrain dataset:** Curated pretrain dataset collected from 46 datasets. Please see [here]() for detail.
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- **Repository:** [repo_url]
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- **Paper :** [paper_url]
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- **Project Page:** https://rdt-robotics.github.io/rdt-robotics/
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## Uses
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RDT takes language instruction, image observations and proprioception as input, and predicts the next 64 robot actions in the form of unified action space vector,
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including all the main physical quantities of robots, including the end-effector and joint, position and velocity, base movement, etc.
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### Getting Started
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RDT-1B supports finetuning on custom dataset, deploying and inferencing on real-robots, as well as pretraining the model.
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Please refer to [our repository](https://github.com/GeneralEmbodiedSystem/RoboticsDiffusionTransformer/blob/main/docs/pretrain.md) for all the above guides.
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